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655,331 | [
"assistants-api",
"function-calling"
] | How to deliver to the user the exact tool output? | "2024-02-26T14:00:40.356000Z" | 7 | 101 | 2 | 0 | 4 | 877 | 894,588 | 2024-02-26T15:33:22.007Z | <p>I don’t understand what you’d be wanting here.</p>
<p>You get the tool_call when it is sent to a tool recipient, with the function name and the function arguments. That’s all you need to both fulfill the request and show the information to a user if they must see.</p>
<p>The AI doesn’t make the API tool object, it has a special backend format that you will never see that is captured and reinterpreted by the API in order to send a tool function to you. OpenAI also goes out of their way to have you provide the call history back within their special message format of “function” so you also aren’t writing the AI’s tokens that it produces to signal a tool.</p>
<p>The fact that a tool call might look like, in AI trained language:<br>
<code>assistant to=wolfram(method) code\n</code> blah blah blah is not of use.</p>
<p>There is no “altering” really. Assistants do have internal function calls to their own tools that are iterative, autonomous, and part of the “agent” behavior.</p> | 15 | 1 | b368833582 | 2 | [
535360,
539078,
500647,
516221,
539421
] | null | I don’t understand what you’d be wanting here.
You get the tool\_call when it is sent to a tool recipient, with the function name and the function arguments. That’s all you need to both fulfill the request and show the information to a user if they must see.
The AI doesn’t make the API tool object, it has a special backend format that you will never see that is captured and reinterpreted by the API in order to send a tool function to you. OpenAI also goes out of their way to have you provide the call history back within their special message format of “function” so you also aren’t writing the AI’s tokens that it produces to signal a tool.
The fact that a tool call might look like, in AI trained language:
`assistant to=wolfram(method) code\n` blah blah blah is not of use.
There is no “altering” really. Assistants do have internal function calls to their own tools that are iterative, autonomous, and part of the “agent” behavior.
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] | assistants-api | function-calling | null | null | https://community.openai.com/t/655331 | https://community.openai.com/p/894588 | Functions (3) | Embeddings (6) |
655,331 | [
"assistants-api",
"function-calling"
] | How to deliver to the user the exact tool output? | "2024-02-26T14:00:40.356000Z" | 7 | 101 | 2 | 0 | 4 | 877 | 894,789 | 2024-02-26T17:09:27.294Z | <p>Hey thank you very much for your reply. I’m sorry but I’m a bit new to these concepts, so I might have said something that doesn’t really make sense.</p>
<p>The point is the following, I am making a chatbot to collect orders from a restaurant, during the conversation I order the product X and Y , the product (and other parameters) are send to the function called order_summary. If I put a fixed string as return of the function, for example “You have order the product J and K”, when the bot replies to the user , the answer is “You have order the product X and Y” and not the product J and K of the fixed string.</p>
<p>The following are part of the code, maybe they can be useful for this.</p>
<pre><code class="lang-auto">
if run_status.status == 'completed':
messages = client.beta.threads.messages.list(thread_id=thread_id)
print("messages:______", messages)
message_content = messages.data[0].content[0].text
# Remove annotations
annotations = message_content.annotations
for annotation in annotations:
message_content.value = message_content.value.replace(
annotation.text, '')
print("Run completed, returning response")
return jsonify({
"response": message_content.value,
"status": "completed"
})
if run_status.status == 'requires_action':
for tool_call in run_status.required_action.submit_tool_outputs.tool_calls:
if tool_call.function.name == "order_summary":
arguments = json.loads(tool_call.function.arguments)
output = functions.order_summary(arguments["prod"],
arguments["order_type"],
arguments["order_payment"],
arguments["address"])
client.beta.threads.runs.submit_tool_outputs(thread_id=thread_id,
run_id=run_id,
tool_outputs=[{
"tool_call_id":
tool_call.id,
"output":
json.dumps(output)
}])
</code></pre>
<pre><code class="lang-auto"> #this is the assistant
assistant = client.beta.assistants.create(
# Change prompting in prompts.py file
instructions=assistant_instructions,
model="gpt-4-1106-preview",
tools=[{
"type": "function",
"function": {
"name": "order_summary",
"description":
"Used to summarize the order when the customer has provided all the necessary information. Never modify the output of this tool",
"parameters": {
"type":
"object",
"properties": {
"prod": {
"type":
"string",
"description":
"List of products ordered by the customer"
},
"order_type": {
"type":
"string",
"description":
"Type of order. Can be Delivery or Pickup"
},
"order_payment": {
"type":
"string",
"description":
"Payment method. Can be Satispay or Cash"
},
"address": {
"type":
"string",
"description":
"Possible delivery address. If not present it is False"
},
},
"required":
["prod", "order_type", "order_payment", "address"]
}
}
}],
#file_ids=[file.id]
)
```
</code></pre> | 13 | 1 | 209a5982d9 | 3 | [
535360,
539078,
500647,
516221,
539421
] | null | Hey thank you very much for your reply. I’m sorry but I’m a bit new to these concepts, so I might have said something that doesn’t really make sense.
The point is the following, I am making a chatbot to collect orders from a restaurant, during the conversation I order the product X and Y , the product (and other parameters) are send to the function called order\_summary. If I put a fixed string as return of the function, for example “You have order the product J and K”, when the bot replies to the user , the answer is “You have order the product X and Y” and not the product J and K of the fixed string.
The following are part of the code, maybe they can be useful for this.
```
if run_status.status == 'completed':
messages = client.beta.threads.messages.list(thread_id=thread_id)
print("messages:______", messages)
message_content = messages.data[0].content[0].text
# Remove annotations
annotations = message_content.annotations
for annotation in annotations:
message_content.value = message_content.value.replace(
annotation.text, '')
print("Run completed, returning response")
return jsonify({
"response": message_content.value,
"status": "completed"
})
if run_status.status == 'requires_action':
for tool_call in run_status.required_action.submit_tool_outputs.tool_calls:
if tool_call.function.name == "order_summary":
arguments = json.loads(tool_call.function.arguments)
output = functions.order_summary(arguments["prod"],
arguments["order_type"],
arguments["order_payment"],
arguments["address"])
client.beta.threads.runs.submit_tool_outputs(thread_id=thread_id,
run_id=run_id,
tool_outputs=[{
"tool_call_id":
tool_call.id,
"output":
json.dumps(output)
}])
```
```
#this is the assistant
assistant = client.beta.assistants.create(
# Change prompting in prompts.py file
instructions=assistant_instructions,
model="gpt-4-1106-preview",
tools=[{
"type": "function",
"function": {
"name": "order_summary",
"description":
"Used to summarize the order when the customer has provided all the necessary information. Never modify the output of this tool",
"parameters": {
"type":
"object",
"properties": {
"prod": {
"type":
"string",
"description":
"List of products ordered by the customer"
},
"order_type": {
"type":
"string",
"description":
"Type of order. Can be Delivery or Pickup"
},
"order_payment": {
"type":
"string",
"description":
"Payment method. Can be Satispay or Cash"
},
"address": {
"type":
"string",
"description":
"Possible delivery address. If not present it is False"
},
},
"required":
["prod", "order_type", "order_payment", "address"]
}
}
}],
#file_ids=[file.id]
)
```
```
| api | neutral | 0.766242 | [
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0.021182304,
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0.09889651,
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] | assistants-api | function-calling | null | null | https://community.openai.com/t/655331 | https://community.openai.com/p/894789 | Functions (2) | Embeddings (6) |
655,331 | [
"assistants-api",
"function-calling"
] | How to deliver to the user the exact tool output? | "2024-02-26T14:00:40.356000Z" | 7 | 101 | 2 | 0 | 4 | 877 | 894,890 | 2024-02-26T17:57:43.110Z | <p>Thank you for the additional information. Can you please share your Assistants’ “Instructions” and the “order_summary” function implementation?</p>
<p>I will need the “order_summary” function to understand what the function’s output looks like, and the Assistants “Instructions” so I can see what changes are necessary to return the “order_summary” output as is.</p> | 12 | 0 | 648a6018e0 | 4 | [
535360,
539078,
500647,
516221,
539421
] | null | Thank you for the additional information. Can you please share your Assistants’ “Instructions” and the “order\_summary” function implementation?
I will need the “order\_summary” function to understand what the function’s output looks like, and the Assistants “Instructions” so I can see what changes are necessary to return the “order\_summary” output as is.
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] | assistants-api | function-calling | null | null | https://community.openai.com/t/655331 | https://community.openai.com/p/894890 | Assistant Tools | Embeddings (6) |
655,331 | [
"assistants-api",
"function-calling"
] | How to deliver to the user the exact tool output? | "2024-02-26T14:00:40.356000Z" | 7 | 101 | 2 | 0 | 4 | 877 | 894,896 | 2024-02-26T18:01:26.209Z | <p>This is a feature that’s been requested numerous times. It’s not possible without bypassing the Assistant framework. If you <em>needed</em> to do it you can send a “OK” to the Assistant and then add the content to another message (if you are handling the conversation yourself, screwed if you are passing responsibility to threads) betraying one source of truth.</p>
<p>Honestly I would just not use Assistants unless you’re willing to wait a year before something usable is implemented. Apparently an update is coming <em>soon</em> but I doubt it addresses anything that people have asked and instead just complicates things.</p>
<p>For context: OP wants to return static content, not to have it spun by GPT. There are obvious use-cases here: if the returned content is long and needs to be repeated verbatim it makes no sense to have GPT churn it, wasting tokens and possibly spinning it.</p>
<p>This <em>could</em> be possible if OpenAI just gave us the ability to create Assistant messages but it’s becoming increasingly obvious that their implementation of the framework prevents this from happening.</p> | 11 | 0 | 883a25e3c6 | 5 | [
535360,
539078,
500647,
516221,
539421
] | null | This is a feature that’s been requested numerous times. It’s not possible without bypassing the Assistant framework. If you *needed* to do it you can send a “OK” to the Assistant and then add the content to another message (if you are handling the conversation yourself, screwed if you are passing responsibility to threads) betraying one source of truth.
Honestly I would just not use Assistants unless you’re willing to wait a year before something usable is implemented. Apparently an update is coming *soon* but I doubt it addresses anything that people have asked and instead just complicates things.
For context: OP wants to return static content, not to have it spun by GPT. There are obvious use-cases here: if the returned content is long and needs to be repeated verbatim it makes no sense to have GPT churn it, wasting tokens and possibly spinning it.
This *could* be possible if OpenAI just gave us the ability to create Assistant messages but it’s becoming increasingly obvious that their implementation of the framework prevents this from happening.
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] | assistants-api | function-calling | null | null | https://community.openai.com/t/655331 | https://community.openai.com/p/894896 | Threads | Embeddings (6) |
655,690 | [
"plugin-development"
] | [Looking for alternative solutions]: Deprecated library (fastapi_async_langchain) | "2024-02-26T17:49:13.649000Z" | 7 | 47 | 0 | 0 | 1 | 56 | 894,874 | 2024-02-26T17:49:13.709Z | <p>Hello OpenAI Community,</p>
<p>I am currently facing an issue with the <code>fastapi_async_langchain</code> library, which seems to no longer be supported. My goal is to maintain the streaming response using FastAPI and Langchain. If anyone has alternative methods please share your recommendations.</p>
<p>Thank you for your assistance. I look forward to learning from the community’s expertise.</p> | 9 | 0 | ed0c271022 | 1 | [
479414,
484499,
320510,
543707,
478439
] | null | Hello OpenAI Community,
I am currently facing an issue with the `fastapi_async_langchain` library, which seems to no longer be supported. My goal is to maintain the streaming response using FastAPI and Langchain. If anyone has alternative methods please share your recommendations.
Thank you for your assistance. I look forward to learning from the community’s expertise.
| api | neutral | 0.516198 | [
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655,329 | [] | Embeddings API Max Batch Size | "2024-02-26T13:59:47.588000Z" | 7 | 70 | 0 | 0 | 2 | 440 | 894,407 | 2024-02-26T13:59:47.651Z | <p>Is there any documentation around what’s the max batch size for the embeddings API? I’m trying to pass batch of texts as input to the API and would like to maximize throughput while respecting the API rate limits.</p> | 12 | 0 | cc4028ebf5 | 1 | [
22422,
86586,
193542,
495332,
76683
] | null | Is there any documentation around what’s the max batch size for the embeddings API? I’m trying to pass batch of texts as input to the API and would like to maximize throughput while respecting the API rate limits.
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] | null | null | null | null | https://community.openai.com/t/655329 | https://community.openai.com/p/894407 | Parallel Methods | Embeddings (6) |
655,329 | [] | Embeddings API Max Batch Size | "2024-02-26T13:59:47.588000Z" | 7 | 70 | 0 | 0 | 2 | 440 | 894,537 | 2024-02-26T15:03:42.860Z | <p>This is an interesting question. Let’s make documentation.</p>
<hr>
<p>[Total tokens for 3-small: 2183 embeddings] Counted: 128026; sending now…</p>
<pre data-code-wrap="patch"><code class="lang-patch">- Embeddings failure Error code: 400 - {'error': {'message': "'$.input' is invalid. Please check the API reference: https://platform.openai.com/docs/api-reference.", 'type': 'invalid_request_error', 'param': None, 'code': None}}`
</code></pre>
<hr>
<p>So we know what fails - and what we don’t have to pay for. After finding success, simple thing to knock of an embedding from the list at a time and see the exact value…</p>
<p>2042:“[2039] It was just dark now. I never went near the”<br>
match score: -0.1131<br>
2043:“[2040] “Good lan’! is dat you, honey? Doan’ make n”<br>
match score: -0.0350<br>
2044:“[2041] It was Jim’s voice—nothing ever sounded so "<br>
match score: -0.0612<br>
2045:”[2042] “Laws bless you, chile, I ’uz right down sh"<br>
match score: -0.0043<br>
2046:“[2043] I says:”<br>
match score: 0.0742<br>
2047:“[2044] “All right—that’s mighty good; they won’t f”<br>
match score: -0.0253</p>
<h2><a name="maximum-embeddings-batch-list-length-2048-1" class="anchor" href="#maximum-embeddings-batch-list-length-2048-1"></a>maximum embeddings batch list length: 2048</h2>
<p>I’ll leave it up to you to max the thing out on <em>8k</em> list <em>items</em> and see…</p> | 10 | 0 | b368833582 | 2 | [
22422,
86586,
193542,
495332,
76683
] | null | This is an interesting question. Let’s make documentation.
---
[Total tokens for 3-small: 2183 embeddings] Counted: 128026; sending now…
```
- Embeddings failure Error code: 400 - {'error': {'message': "'$.input' is invalid. Please check the API reference: https://platform.openai.com/docs/api-reference.", 'type': 'invalid_request_error', 'param': None, 'code': None}}`
```
---
So we know what fails - and what we don’t have to pay for. After finding success, simple thing to knock of an embedding from the list at a time and see the exact value…
2042:“[2039] It was just dark now. I never went near the”
match score: -0.1131
2043:“[2040] “Good lan’! is dat you, honey? Doan’ make n”
match score: -0.0350
2044:“[2041] It was Jim’s voice—nothing ever sounded so "
match score: -0.0612
2045:”[2042] “Laws bless you, chile, I ’uz right down sh"
match score: -0.0043
2046:“[2043] I says:”
match score: 0.0742
2047:“[2044] “All right—that’s mighty good; they won’t f”
match score: -0.0253
maximum embeddings batch list length: 2048
------------------------------------------
I’ll leave it up to you to max the thing out on *8k* list *items* and see…
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] | null | null | null | null | https://community.openai.com/t/655329 | https://community.openai.com/p/894537 | Tokenization | Tokenization (2) |
655,329 | [] | Embeddings API Max Batch Size | "2024-02-26T13:59:47.588000Z" | 7 | 70 | 0 | 0 | 2 | 440 | 894,857 | 2024-02-26T17:41:22.089Z | <p>Looks like <strong>max batch size is 2048</strong></p>
<p>Testing code -</p>
<pre><code class="lang-auto">from openai import OpenAI
def test_max_batch_size(client, batch_sizes):
test_text = "This is a test." # Sample text to duplicate for the batch.
max_supported_batch_size = None
for batch_size in batch_sizes:
try:
texts = [test_text] * batch_size # Create a batch of duplicated texts.
response = client.embeddings.create(
model="text-embedding-3-large",
input=texts,
dimensions=256
)
# If the request is successful, record this batch size as currently the largest successful one.
print(f"Batch size of {batch_size} succeeded.")
max_supported_batch_size = batch_size
except Exception as e:
# Handle specific exceptions or failures based on the API's error responses.
print(f"Batch size of {batch_size} failed with error: {e}")
break # Exit the loop on the first failure.
if max_supported_batch_size:
print(f"Maximum supported batch size is {max_supported_batch_size}")
else:
print("Unable to determine the maximum supported batch size, all tested sizes failed.")
# Example usage
client = OpenAI()
batch_sizes = [2048, 2049, 3072, 4096, 5120, 6144, 7168, 8192, 9216, 10240] # list of batch sizes.
test_max_batch_size(client, batch_sizes)
</code></pre>
<p>Output</p>
<pre><code class="lang-auto">Batch size of 2048 succeeded.
Batch size of 2049 failed with error: Error code: 400 - {'error': {'message': "'$.input' is invalid. Please check the API reference: https://platform.openai.com/docs/api-reference.", 'type': 'invalid_request_error', 'param': None, 'code': None}}
Maximum supported batch size is 2048
</code></pre> | 7 | 0 | cc4028ebf5 | 3 | [
22422,
86586,
193542,
495332,
76683
] | null | Looks like **max batch size is 2048**
Testing code -
```
from openai import OpenAI
def test_max_batch_size(client, batch_sizes):
test_text = "This is a test." # Sample text to duplicate for the batch.
max_supported_batch_size = None
for batch_size in batch_sizes:
try:
texts = [test_text] * batch_size # Create a batch of duplicated texts.
response = client.embeddings.create(
model="text-embedding-3-large",
input=texts,
dimensions=256
)
# If the request is successful, record this batch size as currently the largest successful one.
print(f"Batch size of {batch_size} succeeded.")
max_supported_batch_size = batch_size
except Exception as e:
# Handle specific exceptions or failures based on the API's error responses.
print(f"Batch size of {batch_size} failed with error: {e}")
break # Exit the loop on the first failure.
if max_supported_batch_size:
print(f"Maximum supported batch size is {max_supported_batch_size}")
else:
print("Unable to determine the maximum supported batch size, all tested sizes failed.")
# Example usage
client = OpenAI()
batch_sizes = [2048, 2049, 3072, 4096, 5120, 6144, 7168, 8192, 9216, 10240] # list of batch sizes.
test_max_batch_size(client, batch_sizes)
```
Output
```
Batch size of 2048 succeeded.
Batch size of 2049 failed with error: Error code: 400 - {'error': {'message': "'$.input' is invalid. Please check the API reference: https://platform.openai.com/docs/api-reference.", 'type': 'invalid_request_error', 'param': None, 'code': None}}
Maximum supported batch size is 2048
```
| api | neutral | 0.88881 | [
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] | null | null | null | null | https://community.openai.com/t/655329 | https://community.openai.com/p/894857 | Python3 Packages | Miscellaneous (27) |
648,967 | [
"gpt-4",
"embeddings",
"python"
] | Cannot use a file in post request to openai embedding endpoint | "2024-02-22T20:39:27.206000Z" | 7 | 110 | 1 | 0 | 2 | 236 | 885,984 | 2024-02-22T20:39:27.274Z | <p>Hi all,</p>
<p>When I use this script with a valid bearer token,</p>
<pre><code class="lang-auto">with open('test.json', 'r') as f:
jsonReport = json.load(f)
# print(jsonReport)
data = {
"input": jsonReport,
"model": "text-embedding-ada-002",
"encoding_format": "float"
}
headers = {'Content-Type':'application/json', 'Authorization':'Bearer ' }
x = requests.post(url, data=json.dumps(data), headers=headers)
print(x.text)
</code></pre>
<p>I receive this error:</p>
<pre><code class="lang-auto">{
"error": {
"message": "'$.input' is invalid. Please check the API reference: https://platform.openai.com/docs/api-reference.",
"type": "invalid_request_error",
"param": null,
"code": null
}
}
</code></pre>
<p>this is an example json I am using so its not filesize related…</p>
<pre><code class="lang-auto">{
"element1": ["value1", "value2", "value3"],
"element2": ["value4", "value5", "value6"],
"element3": ["value7", "value8", "value9"],
"element4": ["value10", "value11", "value12"]
}
</code></pre>
<p>I have also tried reading the json as a string and using a var, same issue.</p>
<p>its late and I suspect its my python thats the issue?</p>
<p>thanks</p> | 17 | 1 | 5dada52f1a | 1 | [
494038,
597694,
242454,
489447,
124057
] | null | Hi all,
When I use this script with a valid bearer token,
```
with open('test.json', 'r') as f:
jsonReport = json.load(f)
# print(jsonReport)
data = {
"input": jsonReport,
"model": "text-embedding-ada-002",
"encoding_format": "float"
}
headers = {'Content-Type':'application/json', 'Authorization':'Bearer ' }
x = requests.post(url, data=json.dumps(data), headers=headers)
print(x.text)
```
I receive this error:
```
{
"error": {
"message": "'$.input' is invalid. Please check the API reference: https://platform.openai.com/docs/api-reference.",
"type": "invalid_request_error",
"param": null,
"code": null
}
}
```
this is an example json I am using so its not filesize related…
```
{
"element1": ["value1", "value2", "value3"],
"element2": ["value4", "value5", "value6"],
"element3": ["value7", "value8", "value9"],
"element4": ["value10", "value11", "value12"]
}
```
I have also tried reading the json as a string and using a var, same issue.
its late and I suspect its my python thats the issue?
thanks
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] | gpt-4 | embeddings | python | null | https://community.openai.com/t/648967 | https://community.openai.com/p/885984 | Invalid Request Error | Embeddings (6) |
648,967 | [
"gpt-4",
"embeddings",
"python"
] | Cannot use a file in post request to openai embedding endpoint | "2024-02-22T20:39:27.206000Z" | 7 | 110 | 1 | 0 | 2 | 236 | 886,095 | 2024-02-22T21:27:56.417Z | <aside class="quote no-group" data-username="philprotonphil" data-post="1" data-topic="648967">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://avatars.discourse-cdn.com/v4/letter/p/87869e/48.png" class="avatar"> philprotonphil:</div>
<blockquote>
<pre><code class="lang-auto"> "message": "'$.input' is invalid. Please check the API reference: https://platform.openai.com/docs/api-reference.",
</code></pre>
</blockquote>
</aside>
<p>did you check the url?</p>
<p><a href="https://platform.openai.com/docs/api-reference/embeddings/create?lang=curl" class="onebox" target="_blank" rel="noopener">https://platform.openai.com/docs/api-reference/embeddings/create?lang=curl</a></p>
<p>input needs to be a <em>string</em> or an <em>array</em> - you’re passing an entire object…</p> | 11 | 1 | 69bb4acfca | 2 | [
494038,
597694,
242454,
489447,
124057
] | null |
 philprotonphil:
>
>
> ```
> "message": "'$.input' is invalid. Please check the API reference: https://platform.openai.com/docs/api-reference.",
>
> ```
>
>
did you check the url?
<https://platform.openai.com/docs/api-reference/embeddings/create?lang=curl>
input needs to be a *string* or an *array* - you’re passing an entire object…
| api | neutral | 0.616672 | [
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] | gpt-4 | embeddings | python | null | https://community.openai.com/t/648967 | https://community.openai.com/p/886095 | API | Embeddings (6) |
648,967 | [
"gpt-4",
"embeddings",
"python"
] | Cannot use a file in post request to openai embedding endpoint | "2024-02-22T20:39:27.206000Z" | 7 | 110 | 1 | 0 | 2 | 236 | 894,821 | 2024-02-26T17:24:48.881Z | <p>Thanks, hadn’t realised that - still picking up python and its a million times better than java, but occasionally stuff like this catches me out.</p>
<p>It was the object issue.<br>
I fixed with “input”: json.dumps(jsonReport) for the benefit of others</p>
<p>thanks <img src="https://emoji.discourse-cdn.com/twitter/slight_smile.png?v=12" title=":slight_smile:" class="emoji" alt=":slight_smile:" loading="lazy" width="20" height="20"></p> | 5 | 0 | 5dada52f1a | 3 | [
494038,
597694,
242454,
489447,
124057
] | null | Thanks, hadn’t realised that - still picking up python and its a million times better than java, but occasionally stuff like this catches me out.
It was the object issue.
I fixed with “input”: json.dumps(jsonReport) for the benefit of others
thanks 
| api | positive | 0.415183 | [
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] | gpt-4 | embeddings | python | null | https://community.openai.com/t/648967 | https://community.openai.com/p/894821 | JSON Format | Embeddings (6) |
655,646 | [
"api"
] | How to extract output data to multiple columns and send api calls as batches? | "2024-02-26T17:20:53.754000Z" | 7 | 50 | 0 | 0 | 1 | 306 | 894,816 | 2024-02-26T17:20:53.827Z | <p>Hello everybody,</p>
<p>I have two things that I would like to do for a very big dataset in python:</p>
<ol>
<li>
<p>lets say I have a pandas df with 3 columns. It should take for each row of the df the data from the first column and then it should return using a static prompt the data which gets put in the two other column. Eg input is “apple” → output for the columns “type” and “color”: “fruit, green” → both values are put in the respective columns.<br>
I would love to fill two columns using one api call but I am not sure what separator would work so that it gets correctly split (eg imaging multiple sentences are the result for both columns and not just one word).<br>
Q: Did anyone find a way to do it for multiple columns and which separator works well?</p>
</li>
<li>
<p>I want to not send one individual api call for the case as above, but as a batch so eg 20 calls at the same time. one call contains multiple rows and the response data should get put at the correct row of the df. So the order how the api calls get processed matters in this case. This one I got somewhat to work using concurrent.features in python but its not 100% always working correctly.<br>
Q: did anyone find a way to send a batch of multiple rows to the api where it aksi orders the data correctly back into the df?</p>
</li>
</ol>
<p>For both use-cases I am not 100% how to do it or at least it does not always work. Did anyone already have the same use-cases or tasks for the API and managed to do it successfully? Or do you just send one prompt at a time for each row and column? Thank you very much!</p> | 7 | 0 | d92ab2b47c | 1 | [
41783,
371265,
469304,
33594,
3542
] | null | Hello everybody,
I have two things that I would like to do for a very big dataset in python:
1. lets say I have a pandas df with 3 columns. It should take for each row of the df the data from the first column and then it should return using a static prompt the data which gets put in the two other column. Eg input is “apple” → output for the columns “type” and “color”: “fruit, green” → both values are put in the respective columns.
I would love to fill two columns using one api call but I am not sure what separator would work so that it gets correctly split (eg imaging multiple sentences are the result for both columns and not just one word).
Q: Did anyone find a way to do it for multiple columns and which separator works well?
2. I want to not send one individual api call for the case as above, but as a batch so eg 20 calls at the same time. one call contains multiple rows and the response data should get put at the correct row of the df. So the order how the api calls get processed matters in this case. This one I got somewhat to work using concurrent.features in python but its not 100% always working correctly.
Q: did anyone find a way to send a batch of multiple rows to the api where it aksi orders the data correctly back into the df?
For both use-cases I am not 100% how to do it or at least it does not always work. Did anyone already have the same use-cases or tasks for the API and managed to do it successfully? Or do you just send one prompt at a time for each row and column? Thank you very much!
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] | api | null | null | null | https://community.openai.com/t/655646 | https://community.openai.com/p/894816 | File Management (2) | Embeddings (6) |
491,868 | [] | What is a recommended polling interval for Run object to check the status? | "2023-11-10T06:23:17.738000Z" | 7 | 817 | 1 | 3 | 4 | 189 | 657,233 | 2023-11-10T06:23:17.793Z | <p>Hey everyone,</p>
<p>So, the documentation says, that we should “periodically retrieve the Run object” for updates when we’re dealing with the Assistants API. I wonder, what is a good polling interval (e.g., 1 second)? Also, should I implement a certain timeout in case the status doesn’t change to stop polling? If so what would be a good timeout in seconds? I am probably missing something that the docs already mention. Thanks.</p> | 76 | 0 | 9497b144c0 | 1 | [
507577,
594766,
600070,
577833,
480162
] | null | Hey everyone,
So, the documentation says, that we should “periodically retrieve the Run object” for updates when we’re dealing with the Assistants API. I wonder, what is a good polling interval (e.g., 1 second)? Also, should I implement a certain timeout in case the status doesn’t change to stop polling? If so what would be a good timeout in seconds? I am probably missing something that the docs already mention. Thanks.
| api | neutral | 0.905188 | [
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] | null | null | null | null | https://community.openai.com/t/491868 | https://community.openai.com/p/657233 | Status Updates | API (2) |
491,868 | [] | What is a recommended polling interval for Run object to check the status? | "2023-11-10T06:23:17.738000Z" | 7 | 817 | 1 | 3 | 4 | 189 | 658,560 | 2023-11-10T14:26:49.465Z | <p>I have been polling every 500ms, and time-out after 15000ms. I don’t think there is a “right” answer. It depends on your use-case. I have found Assistant runs to be extremely slow, e.g. anywhere from 3-15+ seconds. So too short of a polling interval would be useless.</p> | 70 | 1 | 54a4178317 | 2 | [
507577,
594766,
600070,
577833,
480162
] | null | I have been polling every 500ms, and time-out after 15000ms. I don’t think there is a “right” answer. It depends on your use-case. I have found Assistant runs to be extremely slow, e.g. anywhere from 3-15+ seconds. So too short of a polling interval would be useless.
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] | null | null | null | null | https://community.openai.com/t/491868 | https://community.openai.com/p/658560 | Performance | Payment (4) |
491,868 | [] | What is a recommended polling interval for Run object to check the status? | "2023-11-10T06:23:17.738000Z" | 7 | 817 | 1 | 3 | 4 | 189 | 658,663 | 2023-11-10T14:47:36.447Z | <p>I am seeing an issue this morning where the run never gets to <code>completed</code> status for some reason.</p>
<p>Anyone else seeing this too?</p> | 70 | 0 | 0e82d0f46f | 3 | [
507577,
594766,
600070,
577833,
480162
] | null | I am seeing an issue this morning where the run never gets to `completed` status for some reason.
Anyone else seeing this too?
| api | negative | 0.677927 | [
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] | null | null | null | null | https://community.openai.com/t/491868 | https://community.openai.com/p/658663 | Status Updates | API (2) |
491,868 | [] | What is a recommended polling interval for Run object to check the status? | "2023-11-10T06:23:17.738000Z" | 7 | 817 | 1 | 3 | 4 | 189 | 894,785 | 2024-02-26T17:08:44.198Z | <p><a class="mention" href="/u/raj5">@raj5</a> I think it might depened on the implementation? I’ve published a library that takes care of this today, so you might want to check this out - it’s <span class="mention">@tmlc</span>/openai-polling on npm, if you’re using JS</p> | 6 | 0 | 4199ddf401 | 4 | [
507577,
594766,
600070,
577833,
480162
] | null | [@raj5](/u/raj5) I think it might depened on the implementation? I’ve published a library that takes care of this today, so you might want to check this out - it’s @tmlc/openai-polling on npm, if you’re using JS
| api | neutral | 0.879541 | [
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] | null | null | null | null | https://community.openai.com/t/491868 | https://community.openai.com/p/894785 | Miscellaneous (6) | Miscellaneous (27) |
611,478 | [
"dalle3"
] | Image generation take longer than before.... why? | "2024-02-02T13:19:40.501000Z" | 7 | 360 | 6 | 0 | 5 | 585 | 834,246 | 2024-02-02T13:19:40.572Z | <p>Hello guys, I have a project that uses dall-e 3 that give me 4 images and I have been using it for quite some time and with good generation times and final results, but about 1 week ago, now the prompts response takes twice as long. Before the responses took between 18 and 25 seconds, now the same takes between 32 and 1 minute or more.</p>
<p>Is there any way to know what is happening or any solution to improve the times with the API - Dall-e 3 ?</p>
<p>Prompts with more text take longer to generate ?</p> | 28 | 1 | 414f77d862 | 1 | [
589702,
23357,
106996,
465566,
97171
] | null | Hello guys, I have a project that uses dall-e 3 that give me 4 images and I have been using it for quite some time and with good generation times and final results, but about 1 week ago, now the prompts response takes twice as long. Before the responses took between 18 and 25 seconds, now the same takes between 32 and 1 minute or more.
Is there any way to know what is happening or any solution to improve the times with the API - Dall-e 3 ?
Prompts with more text take longer to generate ?
| api | neutral | 0.529036 | [
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] | dalle3 | null | null | null | https://community.openai.com/t/611478 | https://community.openai.com/p/834246 | Performance (2) | Tokenization (2) |
611,478 | [
"dalle3"
] | Image generation take longer than before.... why? | "2024-02-02T13:19:40.501000Z" | 7 | 360 | 6 | 0 | 5 | 585 | 834,375 | 2024-02-02T14:06:55.533Z | <aside class="quote no-group quote-modified" data-username="andres.ruz.salinas" data-post="1" data-topic="611478">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/andres.ruz.salinas/48/146472_2.png" class="avatar"> andres.ruz.salinas:</div>
<blockquote>
<p>Do prompts with more text take longer to generate?</p>
</blockquote>
</aside>
<p>This is likely because GPT-4 takes longer to process longer strings of information before passing it onto DALL-E.</p>
<aside class="quote no-group quote-modified" data-username="andres.ruz.salinas" data-post="1" data-topic="611478">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/andres.ruz.salinas/48/146472_2.png" class="avatar"> andres.ruz.salinas:</div>
<blockquote>
<p>Is there any solution to improve the times with the API - Dall-e 3?</p>
</blockquote>
</aside>
<p>The only thing you could do is check your backend/frontend and make sure that nothing on your end is slowing it down.</p> | 26 | 0 | 4774f74cf8 | 2 | [
589702,
23357,
106996,
465566,
97171
] | null |
 andres.ruz.salinas:
>
> Do prompts with more text take longer to generate?
>
>
>
This is likely because GPT-4 takes longer to process longer strings of information before passing it onto DALL-E.
 andres.ruz.salinas:
>
> Is there any solution to improve the times with the API - Dall-e 3?
>
>
>
The only thing you could do is check your backend/frontend and make sure that nothing on your end is slowing it down.
| api | neutral | 0.79179 | [
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] | dalle3 | null | null | null | https://community.openai.com/t/611478 | https://community.openai.com/p/834375 | Performance (2) | Tokenization (2) |
611,478 | [
"dalle3"
] | Image generation take longer than before.... why? | "2024-02-02T13:19:40.501000Z" | 7 | 360 | 6 | 0 | 5 | 585 | 840,060 | 2024-02-05T16:55:03.246Z | <p>Thanks for replying, the truth is that my backend always worked faster for me until recently when it started to work slower. It is taking almost twice as long as it used to.</p>
<p>Now I have a doubt, when using the API to generate Dall-e 3, the prompts are still processed by chat GPT ?</p> | 16 | 2 | 414f77d862 | 3 | [
589702,
23357,
106996,
465566,
97171
] | null | Thanks for replying, the truth is that my backend always worked faster for me until recently when it started to work slower. It is taking almost twice as long as it used to.
Now I have a doubt, when using the API to generate Dall-e 3, the prompts are still processed by chat GPT ?
| api | neutral | 0.449386 | [
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] | dalle3 | null | null | null | https://community.openai.com/t/611478 | https://community.openai.com/p/840060 | GPT4 Playground | GPTs (4) |
611,478 | [
"dalle3"
] | Image generation take longer than before.... why? | "2024-02-02T13:19:40.501000Z" | 7 | 360 | 6 | 0 | 5 | 585 | 844,193 | 2024-02-07T07:54:00.747Z | <p>I used the API to generate 1 image. It took 36 seconds. It took ChatGPT 18 seconds to generate an image with the same prompt.</p> | 15 | 1 | 12590c41b0 | 4 | [
589702,
23357,
106996,
465566,
97171
] | null | I used the API to generate 1 image. It took 36 seconds. It took ChatGPT 18 seconds to generate an image with the same prompt.
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] | dalle3 | null | null | null | https://community.openai.com/t/611478 | https://community.openai.com/p/844193 | Image Recognition | GPTs (4) |
611,478 | [
"dalle3"
] | Image generation take longer than before.... why? | "2024-02-02T13:19:40.501000Z" | 7 | 360 | 6 | 0 | 5 | 585 | 844,204 | 2024-02-07T08:07:12.205Z | <aside class="quote no-group" data-username="andres.ruz.salinas" data-post="3" data-topic="611478">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/andres.ruz.salinas/48/146472_2.png" class="avatar"> andres.ruz.salinas:</div>
<blockquote>
<p>Now I have a doubt, when using the API to generate Dall-e 3, the prompts are still processed by chat GPT ?</p>
</blockquote>
</aside>
<p>You’ll get back a revised_prompt with your DALLE3 API call that shows how your prompt was changed if it was changed…</p>
<p>It’s likely just DALLE3 being used in ChatGPT Plus and Bing and elsewhere for free, and it’s a strain on the system. They’re improving infrastructure, so it’s just an awkward growing stage, hopefully. Hang tight.</p> | 14 | 2 | de2d0a787b | 5 | [
589702,
23357,
106996,
465566,
97171
] | null |
 andres.ruz.salinas:
>
> Now I have a doubt, when using the API to generate Dall-e 3, the prompts are still processed by chat GPT ?
>
>
>
You’ll get back a revised\_prompt with your DALLE3 API call that shows how your prompt was changed if it was changed…
It’s likely just DALLE3 being used in ChatGPT Plus and Bing and elsewhere for free, and it’s a strain on the system. They’re improving infrastructure, so it’s just an awkward growing stage, hopefully. Hang tight.
| api | neutral | 0.803237 | [
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0.028428258,
0.009850034,
-0.05754688,
-0.04936112,
-0.012229329,
0.023201207
] | dalle3 | null | null | null | https://community.openai.com/t/611478 | https://community.openai.com/p/844204 | Image Generation (3) | Artificial Intelligence |
611,478 | [
"dalle3"
] | Image generation take longer than before.... why? | "2024-02-02T13:19:40.501000Z" | 7 | 360 | 6 | 0 | 5 | 585 | 844,709 | 2024-02-07T13:52:36.247Z | <p>So let’s hope it improves and hopefully it won’t take too long since the platform was working better (fast) a few days ago.</p>
<p>Thank you.</p> | 14 | 0 | 414f77d862 | 6 | [
589702,
23357,
106996,
465566,
97171
] | null | So let’s hope it improves and hopefully it won’t take too long since the platform was working better (fast) a few days ago.
Thank you.
| api | positive | 0.881235 | [
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] | dalle3 | null | null | null | https://community.openai.com/t/611478 | https://community.openai.com/p/844709 | Performance | Payment (4) |
611,478 | [
"dalle3"
] | Image generation take longer than before.... why? | "2024-02-02T13:19:40.501000Z" | 7 | 360 | 6 | 0 | 5 | 585 | 844,895 | 2024-02-07T15:52:45.698Z | <p>I have noticed following what you tell me, that every time I send the same prompt to dall-e 3, ChatGPT interferes and generates an image with a reinterpreted prompt, which in many cases, when the prompt is modified by ChatGPT, the image does not comply with what is requested.</p>
<p>It would be interesting to be able to send the promptp to ChatGPT and that this returned prompt can be sent directly to Dall-e 3 avoiding that this new prompt is modified again.</p>
<p>I don’t see the need to reinterpret the prompt each time I send it if I eventually want to generate more images with the same prompt.</p>
<p>I think there are some things that should be given a twist.</p> | 14 | 0 | 414f77d862 | 7 | [
589702,
23357,
106996,
465566,
97171
] | null | I have noticed following what you tell me, that every time I send the same prompt to dall-e 3, ChatGPT interferes and generates an image with a reinterpreted prompt, which in many cases, when the prompt is modified by ChatGPT, the image does not comply with what is requested.
It would be interesting to be able to send the promptp to ChatGPT and that this returned prompt can be sent directly to Dall-e 3 avoiding that this new prompt is modified again.
I don’t see the need to reinterpret the prompt each time I send it if I eventually want to generate more images with the same prompt.
I think there are some things that should be given a twist.
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] | dalle3 | null | null | null | https://community.openai.com/t/611478 | https://community.openai.com/p/844895 | Image Generation (3) | Artificial Intelligence |
611,478 | [
"dalle3"
] | Image generation take longer than before.... why? | "2024-02-02T13:19:40.501000Z" | 7 | 360 | 6 | 0 | 5 | 585 | 865,771 | 2024-02-17T10:36:04.708Z | <p>But you can generate up to 50 images concurrently every 60 seconds with the api. Vs only 2 via GPT.</p> | 11 | 1 | 473bf08b8c | 8 | [
589702,
23357,
106996,
465566,
97171
] | null | But you can generate up to 50 images concurrently every 60 seconds with the api. Vs only 2 via GPT.
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] | dalle3 | null | null | null | https://community.openai.com/t/611478 | https://community.openai.com/p/865771 | Image Recognition | GPTs (4) |
611,478 | [
"dalle3"
] | Image generation take longer than before.... why? | "2024-02-02T13:19:40.501000Z" | 7 | 360 | 6 | 0 | 5 | 585 | 894,780 | 2024-02-26T17:04:42.311Z | <p>According to OpenAI API are at most “dall-e-3 → 15 images per minute” to Tier-4 and “50 images per minute” in Tier 5.</p>
<p>Anyway, this means that there are 30 seconds for each of the 50 generations per minute, since only 1 image can be received per request.</p>
<p>Consider that not all request take the same amount time to respond.</p> | 7 | 0 | 414f77d862 | 9 | [
589702,
23357,
106996,
465566,
97171
] | null | According to OpenAI API are at most “dall-e-3 → 15 images per minute” to Tier-4 and “50 images per minute” in Tier 5.
Anyway, this means that there are 30 seconds for each of the 50 generations per minute, since only 1 image can be received per request.
Consider that not all request take the same amount time to respond.
| api | neutral | 0.910244 | [
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] | dalle3 | null | null | null | https://community.openai.com/t/611478 | https://community.openai.com/p/894780 | Performance (2) | Tokenization (2) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 876,401 | 2024-02-19T23:27:54.366Z | <p>I have a really hard time understanding the documentation for the Assistants, API, what am I missing?<br>
<a href="https://platform.openai.com/docs/assistants/tools/function-calling" class="onebox" target="_blank" rel="noopener nofollow ugc">https://platform.openai.com/docs/assistants/tools/function-calling</a></p>
<pre><code class="lang-auto">assistant = client.beta.assistants.create(
instructions="You are a weather bot. Use the provided functions to answer questions.",
model="gpt-4-turbo-preview",
tools=[{
"type": "function",
"function": {
"name": "getCurrentWeather",
"description": "Get the weather in location",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"},
"unit": {"type": "string", "enum": ["c", "f"]}
},
"required": ["location"]
}
}
}, {
"type": "function",
"function": {
"name": "getNickname",
"description": "Get the nickname of a city",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"},
},
"required": ["location"]
}
}
}]
)
</code></pre>
<ol>
<li>I have built several custom gpts, which has access to API’s that I’ve built, I understand that this the schema for defining functions are similar to that of an openapi schema.</li>
</ol>
<p>But what I dont understand is, is the schema definition provided in the example for actual python code or is it referring to an external api?</p>
<p>It doesn’t make sense in my head that this will refer to python functions for example, what am I missing here?</p>
<p>Where and what is the parameter for defining where said functions are stored?<br>
Is the function definition for REST api calls?</p>
<p>Is it for python functions that I have created and stored on some server or locally? (That doesn’t make sense, I mean, how would it even have access to those functions to begin with if they aren’t exposed through an HTTP endpoint, SSH or some other network protocol, and if that were the case <strong>what parameter indicates how I would even expose the Assistant to said hypothetical functions?</strong>)</p>
<p>I mean yeah, okay, I get it that you are supposed to define the functions here? But okay, where do the <strong>functions come from</strong> ? How do I give the assistant access to functions that I have created?<br>
Is this for defining instructions on how to interact with an api? And if so, WHERE IS THE PARAMETER FOR PUTTING THE ACTUAL HTTP endpoint?</p>
<p>This documentation raises to many questions.</p>
<p>OpenAi: Be better and <strong>make a clearer documentation</strong></p> | 125 | 0 | 5fcff8e663 | 1 | [
500342,
561993,
598123,
587405,
591372
] | null | I have a really hard time understanding the documentation for the Assistants, API, what am I missing?
<https://platform.openai.com/docs/assistants/tools/function-calling>
```
assistant = client.beta.assistants.create(
instructions="You are a weather bot. Use the provided functions to answer questions.",
model="gpt-4-turbo-preview",
tools=[{
"type": "function",
"function": {
"name": "getCurrentWeather",
"description": "Get the weather in location",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"},
"unit": {"type": "string", "enum": ["c", "f"]}
},
"required": ["location"]
}
}
}, {
"type": "function",
"function": {
"name": "getNickname",
"description": "Get the nickname of a city",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"},
},
"required": ["location"]
}
}
}]
)
```
1. I have built several custom gpts, which has access to API’s that I’ve built, I understand that this the schema for defining functions are similar to that of an openapi schema.
But what I dont understand is, is the schema definition provided in the example for actual python code or is it referring to an external api?
It doesn’t make sense in my head that this will refer to python functions for example, what am I missing here?
Where and what is the parameter for defining where said functions are stored?
Is the function definition for REST api calls?
Is it for python functions that I have created and stored on some server or locally? (That doesn’t make sense, I mean, how would it even have access to those functions to begin with if they aren’t exposed through an HTTP endpoint, SSH or some other network protocol, and if that were the case **what parameter indicates how I would even expose the Assistant to said hypothetical functions?**)
I mean yeah, okay, I get it that you are supposed to define the functions here? But okay, where do the **functions come from** ? How do I give the assistant access to functions that I have created?
Is this for defining instructions on how to interact with an api? And if so, WHERE IS THE PARAMETER FOR PUTTING THE ACTUAL HTTP endpoint?
This documentation raises to many questions.
OpenAi: Be better and **make a clearer documentation**
| api | negative | 0.525067 | [
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/876401 | Functions (2) | Embeddings (6) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 876,410 | 2024-02-19T23:34:31.473Z | <p>The Assistant, or any API model creates a universal <em>mock</em> function that you need to validate, clean & process.</p>
<p>I agree though. The documentation is lacking.</p> | 99 | 2 | 883a25e3c6 | 2 | [
500342,
561993,
598123,
587405,
591372
] | null | The Assistant, or any API model creates a universal *mock* function that you need to validate, clean & process.
I agree though. The documentation is lacking.
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/876410 | Assistants, API, Platform | Embeddings (6) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 876,414 | 2024-02-19T23:36:05.705Z | <p>Okay…?</p>
<blockquote>
<p>The Assistant, or any API model creates a <em>mock</em> function that you need to validate, clean & process.</p>
</blockquote>
<p>What does this even mean?</p> | 95 | 1 | 5fcff8e663 | 3 | [
500342,
561993,
598123,
587405,
591372
] | null | Okay…?
>
> The Assistant, or any API model creates a *mock* function that you need to validate, clean & process.
>
>
>
What does this even mean?
| api | neutral | 0.580239 | [
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/876414 | Functions (3) | Embeddings (6) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 876,418 | 2024-02-19T23:37:14.490Z | <aside class="quote no-group" data-username="RonaldGRuckus" data-post="2" data-topic="641440">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/ronaldgruckus/48/228443_2.png" class="avatar"> RonaldGRuckus:</div>
<blockquote>
<p>The Assistant, or any API model creates a universal <em>mock</em> function that you need to validate, clean & process.</p>
</blockquote>
</aside>
<p>I’ll make it as simple as possible:</p>
<ol>
<li>You provide functions</li>
<li>When model determines a function should be called it writes up a mock-up of the function</li>
<li>You need to call the function and return the results</li>
</ol>
<p>It’s really simple. I don’t know why you are trying to be sassy about it. You are over complicating things by trying to relate it to GPTs which make the call for you.</p>
<p>I really don’t want to start to argue so <em>please</em> move this to GPT. Start here:</p>
<p><a href="https://chat.openai.com/share/35b721e0-e378-478d-abdf-4b71af4c8232" class="onebox" target="_blank" rel="noopener nofollow ugc">https://chat.openai.com/share/35b721e0-e378-478d-abdf-4b71af4c8232</a></p>
<p>The only part missed is that once you process the function you return the results to the model</p> | 92 | 1 | 883a25e3c6 | 4 | [
500342,
561993,
598123,
587405,
591372
] | null |
 RonaldGRuckus:
>
> The Assistant, or any API model creates a universal *mock* function that you need to validate, clean & process.
>
>
>
I’ll make it as simple as possible:
1. You provide functions
2. When model determines a function should be called it writes up a mock-up of the function
3. You need to call the function and return the results
It’s really simple. I don’t know why you are trying to be sassy about it. You are over complicating things by trying to relate it to GPTs which make the call for you.
I really don’t want to start to argue so *please* move this to GPT. Start here:
<https://chat.openai.com/share/35b721e0-e378-478d-abdf-4b71af4c8232>
The only part missed is that once you process the function you return the results to the model
| api | neutral | 0.841419 | [
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/876418 | Functions | GPTs (4) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 876,445 | 2024-02-19T23:51:24.578Z | <p>Let say you have this schema:</p>
<pre data-code-wrap="javascript"><code class="lang-javascript">const schema = {
"openapi":"3.1.0",
"info":{
"title":"Wolfram",
"version":"v0.1"
},
"servers":[
{
"url":"https://www.wolframalpha.com",
"description":"Wolfram Server for ChatGPT"
}
],
"paths": {
"/api/v1/cloud-plugin": {
"get": {
"operationId": "getWolframCloudResults",
"externalDocs": "https://reference.wolfram.com/language/",
"summary": "Evaluate Wolfram Language code",
"responses": {
"200": {
"description": "The result of the Wolfram Language evaluation",
"content": {
"text/plain": {}
}
},
"500": {
"description": "Wolfram Cloud was unable to generate a result"
},
"400": {
"description": "The request is missing the 'input' parameter"
},
"403": {
"description": "Unauthorized"
},
"503":{
"description":"Service temporarily unavailable. This may be the result of too many requests."
}
},
"parameters": [
{
"name": "input",
"in": "query",
"description": "the input expression",
"required": true,
"schema": {
"type": "string"
}
}
]
}
},
"/api/v1/llm-api": {
"get":{
"operationId":"getWolframAlphaResults",
"externalDocs":"https://products.wolframalpha.com/api",
"summary":"Get Wolfram|Alpha results",
"responses":{
"200":{
"description":"The result of the Wolfram|Alpha query",
"content":{
"text/plain":{
}
}
},
"400":{
"description":"The request is missing the 'input' parameter"
},
"403":{
"description":"Unauthorized"
},
"500":{
"description":"Wolfram|Alpha was unable to generate a result"
},
"501":{
"description":"Wolfram|Alpha was unable to generate a result"
},
"503":{
"description":"Service temporarily unavailable. This may be the result of too many requests."
}
},
"parameters":[
{
"name":"input",
"in":"query",
"description":"the input",
"required":true,
"schema":{
"type":"string"
}
},
{
"name":"assumption",
"in":"query",
"description":"the assumption to use, passed back from a previous query with the same input.",
"required":false,
"explode":true,
"style":"form",
"schema":{
"type":"array",
"items":{
"type":"string"
}
}
}
]
}
}
}
}
</code></pre>
<p>So you converted them to functions</p>
<pre data-code-wrap="javascript"><code class="lang-javascript">{
"name": "getWolframCloudResults",
"description": "Evaluate Wolfram Language code",
"parameters": {
"type": "object",
"properties": {
"input": {
"type": "string",
"description": "the input expression"
}
},
"required": [
"input"
]
}
}
</code></pre>
<p>and</p>
<pre data-code-wrap="javascript"><code class="lang-javascript"> {
"name": "getWolframAlphaResults",
"description": "Get Wolfram|Alpha results",
"parameters": {
"type": "object",
"properties": {
"input": {
"type": "string",
"description": "the input"
},
"assumption": {
"type": "array",
"description": "the assumption to use, passed back from a previous query with the same input.",
"items": {
"type": "string"
}
}
},
"required": [
"input",
"assumption"
]
}
}
</code></pre>
<p>You attached them to your Assistants API.<br>
Then when you are now polling your Run.</p>
<pre data-code-wrap="javascript"><code class="lang-javascript">let completed = false
do {
const run = await openai.beta.threads.runs.retrieve(threadId, runId)
if(run.status === 'requires_action') {
const tool_calls = run.required_action.submit_tool_outputs.tool_calls
let tool_outputs = []
tool_calls.forEach((tool) => {
const tool_args = JSON.parse(tool.function.arguments)
let tool_output = { status: 'error', message: 'function not found'}
if(tool.function.name === 'getWolframCloudResults') {
// tool_args: { input: '...' }
const response = await fetch(`https://www.wolframalpha.com/api/v1/cloud-plugin?input=${tool_args.input}`)
tool_output = await response.json()
} else if(tool.function.name === 'getWolframAlphaResults') {
// tool_args: { input: '...' , assumtion: [...] }
const response = await fetch(`https://www.wolframalpha.com/api/v1/llm-api?input=${tool_args.input}&assumption=${tool_args.assumption}`)
tool_output = await response.json()
}
tool_outputs.push({
tool_call_id: tool.id,
output: JSON.stringify(tool_output)
})
}
// send back output
await openai.beta.threads.runs.submitToolOutputs(
threadId,
runId,
{
tool_outputs: tool_outputs,
}
} else if(run.status === 'completed') {
// handle completed
completed = true
} else {
// ...
}
await sleep(1000)
} while(!completed)
</code></pre>
<p>You still need to do the fetching to the external API yourself given the parameters from the functions.</p> | 82 | 1 | 2a784e5664 | 5 | [
500342,
561993,
598123,
587405,
591372
] | null | Let say you have this schema:
```
const schema = {
"openapi":"3.1.0",
"info":{
"title":"Wolfram",
"version":"v0.1"
},
"servers":[
{
"url":"https://www.wolframalpha.com",
"description":"Wolfram Server for ChatGPT"
}
],
"paths": {
"/api/v1/cloud-plugin": {
"get": {
"operationId": "getWolframCloudResults",
"externalDocs": "https://reference.wolfram.com/language/",
"summary": "Evaluate Wolfram Language code",
"responses": {
"200": {
"description": "The result of the Wolfram Language evaluation",
"content": {
"text/plain": {}
}
},
"500": {
"description": "Wolfram Cloud was unable to generate a result"
},
"400": {
"description": "The request is missing the 'input' parameter"
},
"403": {
"description": "Unauthorized"
},
"503":{
"description":"Service temporarily unavailable. This may be the result of too many requests."
}
},
"parameters": [
{
"name": "input",
"in": "query",
"description": "the input expression",
"required": true,
"schema": {
"type": "string"
}
}
]
}
},
"/api/v1/llm-api": {
"get":{
"operationId":"getWolframAlphaResults",
"externalDocs":"https://products.wolframalpha.com/api",
"summary":"Get Wolfram|Alpha results",
"responses":{
"200":{
"description":"The result of the Wolfram|Alpha query",
"content":{
"text/plain":{
}
}
},
"400":{
"description":"The request is missing the 'input' parameter"
},
"403":{
"description":"Unauthorized"
},
"500":{
"description":"Wolfram|Alpha was unable to generate a result"
},
"501":{
"description":"Wolfram|Alpha was unable to generate a result"
},
"503":{
"description":"Service temporarily unavailable. This may be the result of too many requests."
}
},
"parameters":[
{
"name":"input",
"in":"query",
"description":"the input",
"required":true,
"schema":{
"type":"string"
}
},
{
"name":"assumption",
"in":"query",
"description":"the assumption to use, passed back from a previous query with the same input.",
"required":false,
"explode":true,
"style":"form",
"schema":{
"type":"array",
"items":{
"type":"string"
}
}
}
]
}
}
}
}
```
So you converted them to functions
```
{
"name": "getWolframCloudResults",
"description": "Evaluate Wolfram Language code",
"parameters": {
"type": "object",
"properties": {
"input": {
"type": "string",
"description": "the input expression"
}
},
"required": [
"input"
]
}
}
```
and
```
{
"name": "getWolframAlphaResults",
"description": "Get Wolfram|Alpha results",
"parameters": {
"type": "object",
"properties": {
"input": {
"type": "string",
"description": "the input"
},
"assumption": {
"type": "array",
"description": "the assumption to use, passed back from a previous query with the same input.",
"items": {
"type": "string"
}
}
},
"required": [
"input",
"assumption"
]
}
}
```
You attached them to your Assistants API.
Then when you are now polling your Run.
```
let completed = false
do {
const run = await openai.beta.threads.runs.retrieve(threadId, runId)
if(run.status === 'requires_action') {
const tool_calls = run.required_action.submit_tool_outputs.tool_calls
let tool_outputs = []
tool_calls.forEach((tool) => {
const tool_args = JSON.parse(tool.function.arguments)
let tool_output = { status: 'error', message: 'function not found'}
if(tool.function.name === 'getWolframCloudResults') {
// tool_args: { input: '...' }
const response = await fetch(`https://www.wolframalpha.com/api/v1/cloud-plugin?input=${tool_args.input}`)
tool_output = await response.json()
} else if(tool.function.name === 'getWolframAlphaResults') {
// tool_args: { input: '...' , assumtion: [...] }
const response = await fetch(`https://www.wolframalpha.com/api/v1/llm-api?input=${tool_args.input}&assumption=${tool_args.assumption}`)
tool_output = await response.json()
}
tool_outputs.push({
tool_call_id: tool.id,
output: JSON.stringify(tool_output)
})
}
// send back output
await openai.beta.threads.runs.submitToolOutputs(
threadId,
runId,
{
tool_outputs: tool_outputs,
}
} else if(run.status === 'completed') {
// handle completed
completed = true
} else {
// ...
}
await sleep(1000)
} while(!completed)
```
You still need to do the fetching to the external API yourself given the parameters from the functions.
| api | neutral | 0.869752 | [
0.012904751,
0.06534051,
-0.11323795,
-0.08534039,
0.04443155,
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/876445 | Error Handling | Embeddings (6) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 876,450 | 2024-02-19T23:54:59.928Z | <p>Wasn’t trying to be sassy, genuinely confused.<br>
Did find this article however, for anyone who might stumble upon this post in a google search:</p><aside class="onebox allowlistedgeneric" data-onebox-src="https://cookbook.openai.com/examples/how_to_call_functions_with_chat_models">
<header class="source">
<img src="https://cookbook.openai.com/favicon.svg" class="site-icon" width="500" height="500">
<a href="https://cookbook.openai.com/examples/how_to_call_functions_with_chat_models" target="_blank" rel="noopener nofollow ugc">cookbook.openai.com</a>
</header>
<article class="onebox-body">
<div class="aspect-image" style="--aspect-ratio:690/379;"><img src="https://global.discourse-cdn.com/openai1/original/3X/2/0/20c02719de460572413c0ccfa7342a4ca8d7f868.png" class="thumbnail" data-dominant-color="F4F4F4" width="690" height="379"></div>
<h3><a href="https://cookbook.openai.com/examples/how_to_call_functions_with_chat_models" target="_blank" rel="noopener nofollow ugc">How to call functions with chat models | OpenAI Cookbook</a></h3>
<p>Open-source examples and guides for building with the OpenAI API. Browse a collection of snippets, advanced techniques and walkthroughs. Share your own examples and guides.</p>
</article>
<div class="onebox-metadata">
</div>
<div style="clear: both"></div>
</aside>
<p>It seems to explain some of the things that I am missing.<br>
So when you are using the chat completion you can define utility functions (such as sqlite functions for querying a database, as is used as an example in the cookbook article). And we use the tools parameter to instruct the model to when and how to use these specific python functions, which is defined in the function schema definition. So in the part of the code where the gpt-4 model is used we call the function in the same file? (At least from what i can see in the cookbook example )<br>
Hmm… Okay, I guess i’ll have to burn through some OpenAi credits before I get the hang of this…</p>
<p>Still a little bit confused</p> | 69 | 2 | 5fcff8e663 | 6 | [
500342,
561993,
598123,
587405,
591372
] | null | Wasn’t trying to be sassy, genuinely confused.
Did find this article however, for anyone who might stumble upon this post in a google search:
[cookbook.openai.com](https://cookbook.openai.com/examples/how_to_call_functions_with_chat_models)
### [How to call functions with chat models | OpenAI Cookbook](https://cookbook.openai.com/examples/how_to_call_functions_with_chat_models)
Open-source examples and guides for building with the OpenAI API. Browse a collection of snippets, advanced techniques and walkthroughs. Share your own examples and guides.
It seems to explain some of the things that I am missing.
So when you are using the chat completion you can define utility functions (such as sqlite functions for querying a database, as is used as an example in the cookbook article). And we use the tools parameter to instruct the model to when and how to use these specific python functions, which is defined in the function schema definition. So in the part of the code where the gpt-4 model is used we call the function in the same file? (At least from what i can see in the cookbook example )
Hmm… Okay, I guess i’ll have to burn through some OpenAi credits before I get the hang of this…
Still a little bit confused
| api | neutral | 0.725897 | [
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/876450 | Assistant | Miscellaneous (27) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 876,454 | 2024-02-19T23:56:05.919Z | <p>Ohhhh! Okay, I see now. This explains a lot, thanks</p> | 65 | 0 | 5fcff8e663 | 7 | [
500342,
561993,
598123,
587405,
591372
] | null | Ohhhh! Okay, I see now. This explains a lot, thanks
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/876454 | Legal Proceedings | Emoji (8) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 876,459 | 2024-02-19T23:58:40.967Z | <p>Ok. Sorry for the assumption.</p>
<p>You’re kind of on the right track. I believe the confusion comes from using GPTs first.</p>
<p>The functions are universal. It doesn’t need to be Python or anything. You are (usually) using the same code that manages your logic to also perform the functions.</p>
<p>The GPTs make the call on your behalf (because you aren’t managing them) so there’s a lot more going on.</p> | 64 | 1 | 883a25e3c6 | 8 | [
500342,
561993,
598123,
587405,
591372
] | null | Ok. Sorry for the assumption.
You’re kind of on the right track. I believe the confusion comes from using GPTs first.
The functions are universal. It doesn’t need to be Python or anything. You are (usually) using the same code that manages your logic to also perform the functions.
The GPTs make the call on your behalf (because you aren’t managing them) so there’s a lot more going on.
| api | neutral | 0.710966 | [
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/876459 | Functions | GPTs (4) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 876,468 | 2024-02-20T00:04:22.230Z | <blockquote>
<p>You’re kind of on the right track. I believe the confusion comes from using GPTs first.</p>
</blockquote>
<p>Yea most likely, the docs for the custom gpt is extremely simple and straightforward, it makes sense.<br>
Well… it’s going to be fun to integrate over 30 different endpoints into this now. My openapi.yaml file is already 1500 lines long.</p>
<p>I wonder of OpenAi makes a lot of money from newbie junior devs like me, like, I have already payed like 20 dollars to openai now, and thats only when I did like 3-4 tests to see if my code worked properly.</p> | 61 | 1 | 5fcff8e663 | 9 | [
500342,
561993,
598123,
587405,
591372
] | null |
>
> You’re kind of on the right track. I believe the confusion comes from using GPTs first.
>
>
>
Yea most likely, the docs for the custom gpt is extremely simple and straightforward, it makes sense.
Well… it’s going to be fun to integrate over 30 different endpoints into this now. My openapi.yaml file is already 1500 lines long.
I wonder of OpenAi makes a lot of money from newbie junior devs like me, like, I have already payed like 20 dollars to openai now, and thats only when I did like 3-4 tests to see if my code worked properly.
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/876468 | Miscellaneous (26) | GPTs (4) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 876,482 | 2024-02-20T00:11:16.175Z | <p>The good news is that with such a large amount of functions to call you can practice with GPTs. Ensure a consistent experience, move onto the API & you can fine-tune the function calling to reduce costs (as all of these functions are sent with each message).</p>
<p>The schema for function calling is much more distilled as well.</p>
<p>Good luck in your coding</p> | 60 | 1 | 883a25e3c6 | 10 | [
500342,
561993,
598123,
587405,
591372
] | null | The good news is that with such a large amount of functions to call you can practice with GPTs. Ensure a consistent experience, move onto the API & you can fine-tune the function calling to reduce costs (as all of these functions are sent with each message).
The schema for function calling is much more distilled as well.
Good luck in your coding
| api | positive | 0.876516 | [
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/876482 | Functions | GPTs (4) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 876,608 | 2024-02-20T01:26:44.917Z | <p>I’ll explain it a bit better.</p>
<h2><a name="assistants-functions-tools-1" class="anchor" href="#assistants-functions-tools-1"></a>Assistants - Functions (tools)</h2>
<h3><a name="defining-functions-in-assistants-2" class="anchor" href="#defining-functions-in-assistants-2"></a>Defining Functions in Assistants</h3>
<ul>
<li>When you <strong>create</strong> the definition and operation method of an assistant with a <code>assistants.create</code> API method or “assistants” base url call, you provide a tools specification, which can have a list of functions you created, and/or a list of built-in tools.</li>
<li>When you write the <strong>functions</strong>’ specification, it must adhere to a particular object schema, that has the name, and the parameters the AI can specify when sending.</li>
<li>Function specification is not received by the AI as it is written in json. The function is parsed, and only particular keys, such as “description” are included. That means examples, maximum values, etc, might not be rejected, but are never be seen. The text <strong>descriptions</strong> of exactly what the function is meant to achieve and return, and the parameter <strong>names</strong> are paramount to AI understanding.</li>
</ul>
<h3><a name="receiving-functions-3" class="anchor" href="#receiving-functions-3"></a>Receiving Functions</h3>
<ul>
<li>When the AI has found that a user input could benefit from, or could be directly addressed by, a function specified by the developer, AI will send a <strong>message</strong> to the function name instead of sending a message to be read by a user (on chat completions AI may combine them, but this seems trained out).</li>
<li>You make continued polling requests for runs.retrieve, or a URL with the run ID. This gives you information about the progress of the run.</li>
<li>When when the run status is updated by the AI calling for function(s), instead of <code>completed</code>, you will receive <code>requires_action</code>. This indicates a function request is available.</li>
<li>You then parse that run object, which will now contain a <code> "required_action"</code> object, in tools format, with a list of all functions the AI wants to call in parallel. Parse them out.</li>
</ul>
<p>Note: the parameters that are emitted originate directly from an AI-written JSON. The AI’s ability to understand the specification and create this is important.</p>
<h3><a name="returning-functions-4" class="anchor" href="#returning-functions-4"></a>Returning functions</h3>
<ul>
<li><strong>fulfill</strong> the request <strong>with your own code</strong>. Make any external requests to APIs that you employ <strong>with your own internet</strong>.</li>
<li>the AI is encouraged to make use of multiple functions at once, expect this.</li>
<li>create the <strong>return object</strong> with all responses and matching ids to what was emitted.</li>
<li>send the tool object to the API with the runs.<strong>submit_tool_outputs</strong>.</li>
<li>the run continues if the form of what you sent is not rejected.</li>
<li>continue to poll for status.</li>
</ul>
<p>I hope this tediously human-written explanation serves you. It overlaps the <a href="https://platform.openai.com/docs/assistants/tools">Documentation</a> and API reference (which have many back-and-forth references between themselves required for understanding.)</p>
<p>When you have written your own tools, you then can also replace those that are built in. The tedium of a dozen assistants API methods then becomes preposterous compared to owning your own <em>chat completions</em> code you can supervise.</p> | 63 | 0 | b368833582 | 11 | [
500342,
561993,
598123,
587405,
591372
] | null | I’ll explain it a bit better.
Assistants - Functions (tools)
------------------------------
### Defining Functions in Assistants
* When you **create** the definition and operation method of an assistant with a `assistants.create` API method or “assistants” base url call, you provide a tools specification, which can have a list of functions you created, and/or a list of built-in tools.
* When you write the **functions**’ specification, it must adhere to a particular object schema, that has the name, and the parameters the AI can specify when sending.
* Function specification is not received by the AI as it is written in json. The function is parsed, and only particular keys, such as “description” are included. That means examples, maximum values, etc, might not be rejected, but are never be seen. The text **descriptions** of exactly what the function is meant to achieve and return, and the parameter **names** are paramount to AI understanding.
### Receiving Functions
* When the AI has found that a user input could benefit from, or could be directly addressed by, a function specified by the developer, AI will send a **message** to the function name instead of sending a message to be read by a user (on chat completions AI may combine them, but this seems trained out).
* You make continued polling requests for runs.retrieve, or a URL with the run ID. This gives you information about the progress of the run.
* When when the run status is updated by the AI calling for function(s), instead of `completed`, you will receive `requires_action`. This indicates a function request is available.
* You then parse that run object, which will now contain a `"required_action"` object, in tools format, with a list of all functions the AI wants to call in parallel. Parse them out.
Note: the parameters that are emitted originate directly from an AI-written JSON. The AI’s ability to understand the specification and create this is important.
### Returning functions
* **fulfill** the request **with your own code**. Make any external requests to APIs that you employ **with your own internet**.
* the AI is encouraged to make use of multiple functions at once, expect this.
* create the **return object** with all responses and matching ids to what was emitted.
* send the tool object to the API with the runs.**submit\_tool\_outputs**.
* the run continues if the form of what you sent is not rejected.
* continue to poll for status.
I hope this tediously human-written explanation serves you. It overlaps the [Documentation](https://platform.openai.com/docs/assistants/tools) and API reference (which have many back-and-forth references between themselves required for understanding.)
When you have written your own tools, you then can also replace those that are built in. The tedium of a dozen assistants API methods then becomes preposterous compared to owning your own *chat completions* code you can supervise.
| api | neutral | 0.875698 | [
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/876608 | Functions (3) | Embeddings (6) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 880,452 | 2024-02-21T02:49:28.383Z | <p>How do you fine-tune an assistant, specifically for function calling? Is it the same process as the <a href="https://platform.openai.com/docs/guides/fine-tuning" rel="noopener nofollow ugc">completions fine-tuning</a>?</p> | 44 | 1 | 59449695ef | 12 | [
500342,
561993,
598123,
587405,
591372
] | null | How do you fine-tune an assistant, specifically for function calling? Is it the same process as the [completions fine-tuning](https://platform.openai.com/docs/guides/fine-tuning)?
| api | neutral | 0.895291 | [
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/880452 | Assistant Tools | Embeddings (6) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 880,563 | 2024-02-21T03:51:14.150Z | <p>Fine-tune models cannot be used in the Assistants endpoint.</p>
<p>Developer fine-tunes are more likely to damage the function training than to improve it, without devoting experienced labor to the development of training example sets (one discovers when they are used on the chat completions endpoint).</p>
<p>For improving the quality of tool-calling, you have the function specification itself, the name and the parameter names within, and the description text of parameters, to make the utility of the function and the expected return value extremely clear to the AI.</p> | 44 | 0 | b368833582 | 13 | [
500342,
561993,
598123,
587405,
591372
] | null | Fine-tune models cannot be used in the Assistants endpoint.
Developer fine-tunes are more likely to damage the function training than to improve it, without devoting experienced labor to the development of training example sets (one discovers when they are used on the chat completions endpoint).
For improving the quality of tool-calling, you have the function specification itself, the name and the parameter names within, and the description text of parameters, to make the utility of the function and the expected return value extremely clear to the AI.
| api | negative | 0.558667 | [
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/880563 | Functions (3) | Embeddings (6) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 881,080 | 2024-02-21T07:30:50.755Z | <p>Anyone have an idea if there is a community sharing some simple functions? This thread did help me undersatnd the function calling better, but i feel many calls will be rather similar so just wondering if there was a community share.<br>
I’m looking to create PPT from discussion, but having difficulty actually getting the function call to work</p> | 43 | 0 | 5f30168770 | 14 | [
500342,
561993,
598123,
587405,
591372
] | null | Anyone have an idea if there is a community sharing some simple functions? This thread did help me undersatnd the function calling better, but i feel many calls will be rather similar so just wondering if there was a community share.
I’m looking to create PPT from discussion, but having difficulty actually getting the function call to work
| api | neutral | 0.638456 | [
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/881080 | Functions (4) | Embeddings (6) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 882,612 | 2024-02-21T17:36:16.915Z | <p>After using function calling for the last month, I wanted to provide my thoughts on how to effectively use it.</p>
<ul>
<li>
<p>most of the time the LLM should be calling one or more APIs (which is disguised as a function). I normally wrap these in python requests functions which call a FastAPI endpoing. This approach is tedious BUT generates really good results. I personally use the Llama-Index wrapper on the OpenAI Agent, which has multi-turn single function calling. This allows the function calling to be self-organized by the LLM.</p>
</li>
<li>
<p>It does seem that you can provide an executable function, I don’t really know how or why this works. For example you can pass in a simple add or subtract python function and it will execute it on your behalf. I think its calling an eval(“python code”) on the local python kernel or using code interpreter to run the functions. The reason this doesn’t work well for my use cases is that I am usually performing Retrieval, which requires a dependency. The dependency doesn’t seem to work in the executable python function hence the main reason I wrap the tool in an API.</p>
</li>
</ul>
<p>By adopting this belief, I was able to organize my project so that there is a many to many relationship between functions to be called an agents. You can also nest agents within function calling (think http request):</p>
<p>├── backend<br>
│ ├── agents<br>
│ │ ├── analyst<br>
│ │ └── zendesk<br>
│ │ ├── agent.py<br>
│ │ ├── Dockerfile<br>
│ │ ├── main.py<br>
│ │ ├── requirements.txt<br>
│ │ ├── router.py<br>
│ │ └── utils.py<br>
│ └── data<br>
│ ├── data_dictionary<br>
│ ├── zendesk<br>
│ ├── Dockerfile<br>
│ ├── main.py<br>
│ └── requirements.txt<br>
├── frontend<br>
├── notebooks<br>
├── pipeline<br>
└── README.md</p> | 41 | 0 | 91652435f5 | 15 | [
500342,
561993,
598123,
587405,
591372
] | null | After using function calling for the last month, I wanted to provide my thoughts on how to effectively use it.
* most of the time the LLM should be calling one or more APIs (which is disguised as a function). I normally wrap these in python requests functions which call a FastAPI endpoing. This approach is tedious BUT generates really good results. I personally use the Llama-Index wrapper on the OpenAI Agent, which has multi-turn single function calling. This allows the function calling to be self-organized by the LLM.
* It does seem that you can provide an executable function, I don’t really know how or why this works. For example you can pass in a simple add or subtract python function and it will execute it on your behalf. I think its calling an eval(“python code”) on the local python kernel or using code interpreter to run the functions. The reason this doesn’t work well for my use cases is that I am usually performing Retrieval, which requires a dependency. The dependency doesn’t seem to work in the executable python function hence the main reason I wrap the tool in an API.
By adopting this belief, I was able to organize my project so that there is a many to many relationship between functions to be called an agents. You can also nest agents within function calling (think http request):
├── backend
│ ├── agents
│ │ ├── analyst
│ │ └── zendesk
│ │ ├── agent.py
│ │ ├── Dockerfile
│ │ ├── main.py
│ │ ├── requirements.txt
│ │ ├── router.py
│ │ └── utils.py
│ └── data
│ ├── data\_dictionary
│ ├── zendesk
│ ├── Dockerfile
│ ├── main.py
│ └── requirements.txt
├── frontend
├── notebooks
├── pipeline
└── README.md
| api | neutral | 0.698992 | [
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/882612 | Functions (4) | Embeddings (6) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 885,382 | 2024-02-22T16:11:02.852Z | <p>Another take…<br>
You provide the LLM with the definition or blueprint of a function you have. The example they use is the get weather function that takes in a location parameter.<br>
Once GPT determines it should call this function to generate a better response, it will reply to you (the thing/system sending/processing these Open AI API calls) with a function message that essentially tells your code - “Hey, run this function and return the results to me”.<br>
Your code sees this message and knows (you programmed it) to call the function (remember, you told it you have these functions) and return the results via a special <code>function</code> message.</p>
<p>I think one misconception is that OpenAI/GPT is actually calling a function for you in their system.</p>
<p>In the case of the get weather example they use, they call a 3rd party weather API from the example code in a similar process as I described above.</p> | 34 | 0 | 14ac7d0a8a | 16 | [
500342,
561993,
598123,
587405,
591372
] | null | Another take…
You provide the LLM with the definition or blueprint of a function you have. The example they use is the get weather function that takes in a location parameter.
Once GPT determines it should call this function to generate a better response, it will reply to you (the thing/system sending/processing these Open AI API calls) with a function message that essentially tells your code - “Hey, run this function and return the results to me”.
Your code sees this message and knows (you programmed it) to call the function (remember, you told it you have these functions) and return the results via a special `function` message.
I think one misconception is that OpenAI/GPT is actually calling a function for you in their system.
In the case of the get weather example they use, they call a 3rd party weather API from the example code in a similar process as I described above.
| api | neutral | 0.833457 | [
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/885382 | Functions (3) | Embeddings (6) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 888,030 | 2024-02-23T14:27:56.098Z | <p>(post deleted by author)</p> | 24 | 0 | a5b08ac443 | 17 | [
500342,
561993,
598123,
587405,
591372
] | null | (post deleted by author)
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/888030 | Moderation | Emoji (8) |
641,440 | [
"gpt-4",
"api",
"assistants-api"
] | How does function calling actually work for the Assistants API? | "2024-02-19T23:27:54.285000Z" | 7 | 857 | 10 | 9 | 10 | 2,547 | 894,778 | 2024-02-26T17:03:50.170Z | <p>I hope this helps anyone looking for how to do polling for Assistants API and Threads API - a package <span class="mention">@tmlc</span>/openai-polling on npm and TinyMLCompany/openai-polling on GitHub</p> | 9 | 0 | 4199ddf401 | 18 | [
500342,
561993,
598123,
587405,
591372
] | null | I hope this helps anyone looking for how to do polling for Assistants API and Threads API - a package @tmlc/openai-polling on npm and TinyMLCompany/openai-polling on GitHub
| api | positive | 0.725026 | [
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] | gpt-4 | api | assistants-api | null | https://community.openai.com/t/641440 | https://community.openai.com/p/894778 | GitHub | Miscellaneous (27) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 647,107 | 2023-11-08T17:06:09.393Z | <p>When you execute a run command, the run is queued and according to the documentation:<br>
"You can periodically retrieve the Run to check on its <a href="https://platform.openai.com/docs/assistants/how-it-works/run-lifecycle" rel="noopener nofollow ugc">status</a> to see if it has moved to <code>completed</code> ".</p>
<p>This is a good candidate for webhook. Instead of pooling results, it would be better for the system to inform me (via a webhook) when the task has completed.<br>
Thanks,<br>
Jonathan Ekwempu</p> | 182 | 1 | 3bd1b272d0 | 1 | [
478937,
499916,
578711,
542300,
502525
] | null | When you execute a run command, the run is queued and according to the documentation:
"You can periodically retrieve the Run to check on its [status](https://platform.openai.com/docs/assistants/how-it-works/run-lifecycle) to see if it has moved to `completed` ".
This is a good candidate for webhook. Instead of pooling results, it would be better for the system to inform me (via a webhook) when the task has completed.
Thanks,
Jonathan Ekwempu
| api | neutral | 0.672614 | [
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/647107 | Status Updates | API (2) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 652,352 | 2023-11-09T11:41:08.107Z | <p>I think webhooks would be great for this! Until we have a better solution than pooling - do you currently have any strategy for pooling results? I planned on doing it every few seconds, but I don’t want to keep users waiting for the answer more than necessary.</p>
<p>Also, I can’t seem to find this anywhere, are Assistant API calls free? Does it matter (pricing-wise) if I pool it every second or every 10 seconds?</p> | 168 | 1 | fda17a81e7 | 2 | [
478937,
499916,
578711,
542300,
502525
] | null | I think webhooks would be great for this! Until we have a better solution than pooling - do you currently have any strategy for pooling results? I planned on doing it every few seconds, but I don’t want to keep users waiting for the answer more than necessary.
Also, I can’t seem to find this anywhere, are Assistant API calls free? Does it matter (pricing-wise) if I pool it every second or every 10 seconds?
| api | positive | 0.550215 | [
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/652352 | Parallel Methods | Embeddings (6) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 652,369 | 2023-11-09T11:43:50.158Z | <aside class="quote no-group" data-username="onyii5119" data-post="1" data-topic="484418">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://avatars.discourse-cdn.com/v4/letter/o/e68b1a/48.png" class="avatar"> onyii5119:</div>
<blockquote>
<p>This is a good candidate for webhook. Instead of pooling results, it would be better for the system to inform me (via a webhook) when the task has completed.</p>
</blockquote>
</aside>
<p>Can’t the model be instructed to do that now via a function?</p> | 163 | 1 | 9716394c2d | 3 | [
478937,
499916,
578711,
542300,
502525
] | null |
 onyii5119:
>
> This is a good candidate for webhook. Instead of pooling results, it would be better for the system to inform me (via a webhook) when the task has completed.
>
>
>
Can’t the model be instructed to do that now via a function?
| api | neutral | 0.705906 | [
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/652369 | Functions (4) | Embeddings (6) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 652,463 | 2023-11-09T11:52:40.326Z | <p>I don’t see how, do you maybe have an example?</p> | 155 | 1 | fda17a81e7 | 5 | [
478937,
499916,
578711,
542300,
502525
] | null | I don’t see how, do you maybe have an example?
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/652463 | Chess | Artificial Intelligence |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 655,530 | 2023-11-09T19:34:49.385Z | <p>I have not done function calling myself so far as I’ve not had the need. But, this would be my approach to do it:</p>
<p>According to the Assistants API overview, this API " the API allows you to define custom function signatures, with similar behavior as our <a href="https://openai.com/blog/function-calling-and-other-api-updates" rel="noopener nofollow ugc">function calling</a> feature." <a href="https://platform.openai.com/docs/assistants/overview" class="inline-onebox" rel="noopener nofollow ugc">OpenAI Platform</a></p>
<p>So, in my API Instructions, I would include a prompt to “please send notification of your response” or something to that effect. I would then included a function which will send the current thread ID to some webhook.</p>
<p>That webhook would be designed to simply send a polling request to the thread id which should, theoretically, return the assistant’s response.</p>
<p>Of course, someone who has actually used functions will be able to provide a more detailed example.</p> | 151 | 1 | 9716394c2d | 6 | [
478937,
499916,
578711,
542300,
502525
] | null | I have not done function calling myself so far as I’ve not had the need. But, this would be my approach to do it:
According to the Assistants API overview, this API " the API allows you to define custom function signatures, with similar behavior as our [function calling](https://openai.com/blog/function-calling-and-other-api-updates) feature." [OpenAI Platform](https://platform.openai.com/docs/assistants/overview)
So, in my API Instructions, I would include a prompt to “please send notification of your response” or something to that effect. I would then included a function which will send the current thread ID to some webhook.
That webhook would be designed to simply send a polling request to the thread id which should, theoretically, return the assistant’s response.
Of course, someone who has actually used functions will be able to provide a more detailed example.
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/655530 | Functions (3) | Embeddings (6) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 655,637 | 2023-11-09T20:06:38.518Z | <p>Hi <a class="mention" href="/u/somebodysysop">@SomebodySysop</a>, thanks for your feedback. I don’t think using functions is a suitable solution for this kind of problem. You can even see from your response that the “webhook should be designed to do some form of polling”. That really negates the whole purpose of a webhook. Ideally, you “push” to a webhook. A webhook does not really request data. Any solution that requires polling is not right in my opinion.</p> | 143 | 1 | 3bd1b272d0 | 7 | [
478937,
499916,
578711,
542300,
502525
] | null | Hi [@SomebodySysop](/u/somebodysysop), thanks for your feedback. I don’t think using functions is a suitable solution for this kind of problem. You can even see from your response that the “webhook should be designed to do some form of polling”. That really negates the whole purpose of a webhook. Ideally, you “push” to a webhook. A webhook does not really request data. Any solution that requires polling is not right in my opinion.
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/655637 | Search Engine Optimization (SEO) | Embeddings (6) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 655,642 | 2023-11-09T20:08:54.741Z | <p>Oh, yes, you’re right. Just push the whole response back. Why didn’t I think of that.</p>
<p>Also, it’s not functions apparently with assistant api, it’s “actions”. <a href="https://community.openai.com/t/custom-gpts-with-custom-actions/490485/3" class="inline-onebox">Custom GPTs with Custom Actions - #3 by andrew.demerchant</a></p> | 137 | 0 | 9716394c2d | 8 | [
478937,
499916,
578711,
542300,
502525
] | null | Oh, yes, you’re right. Just push the whole response back. Why didn’t I think of that.
Also, it’s not functions apparently with assistant api, it’s “actions”. [Custom GPTs with Custom Actions - #3 by andrew.demerchant](https://community.openai.com/t/custom-gpts-with-custom-actions/490485/3)
| api | neutral | 0.56602 | [
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/655642 | Assistant Tools | Embeddings (6) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 677,976 | 2023-11-16T03:43:07.465Z | <p>Ok, I’m pretty sure that there is no way to call a webhook. The documentation around calling a function calls a function <strong>in your program</strong>, not a function that exists on the OpenAI side. I had a bit of fun with GPTs in deciding this was the case. I made an “Assistants API Knower” GPT that has all of the current Assistants API documentation and a zip of the openai-python 1.3 code dumped into it. You have to constantly remind it to refer to its knowledge base, but it does a good job of helping write Assistants API code.</p>
<p>Ugh, I can’t add links to a post, so I can’t share it. I’ll tweet about it – <a class="mention" href="/u/johnnylambada">@johnnylambada</a></p> | 104 | 0 | 2f54fb6d28 | 10 | [
478937,
499916,
578711,
542300,
502525
] | null | Ok, I’m pretty sure that there is no way to call a webhook. The documentation around calling a function calls a function **in your program**, not a function that exists on the OpenAI side. I had a bit of fun with GPTs in deciding this was the case. I made an “Assistants API Knower” GPT that has all of the current Assistants API documentation and a zip of the openai-python 1.3 code dumped into it. You have to constantly remind it to refer to its knowledge base, but it does a good job of helping write Assistants API code.
Ugh, I can’t add links to a post, so I can’t share it. I’ll tweet about it – [@johnnylambada](/u/johnnylambada)
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/677976 | PHP Libraries | Miscellaneous (27) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 703,978 | 2023-11-24T14:02:59.206Z | <p>As mentioned on <a href="https://platform.openai.com/docs/assistants/how-it-works/runs-and-run-steps" rel="noopener nofollow ugc">https://platform.openai.com/docs/assistants/how-it-works/runs-and-run-steps</a>, “… You can check the status of the run each time you retrieve the object to determine what your application should do next.”</p>
<p>Background: We are building a support assistant, leveraging Retrieval tool & Assistant API in the backend. We will be using a Bot from one of the Chat Solution 3rd parties and configure our platform Bot in it. The Bot will receive, end users’ queries and will then leverage the Assistant API (with Knowledge Retrieval tool, we’re adding a knowledge base file with Assistant for augmentation) before ‘asynchronously’ responding back to end user message.</p>
<p>Question: How to design a performant and scalable solution where our backend server will receive end user’s queries and it asynchronously passes it to Assistant API for responses - we’re looking for suggestions for how best to implement this polling mechanism since it seems we need to poll for every run separately.</p> | 86 | 1 | 8460448b05 | 11 | [
478937,
499916,
578711,
542300,
502525
] | null | As mentioned on <https://platform.openai.com/docs/assistants/how-it-works/runs-and-run-steps>, “… You can check the status of the run each time you retrieve the object to determine what your application should do next.”
Background: We are building a support assistant, leveraging Retrieval tool & Assistant API in the backend. We will be using a Bot from one of the Chat Solution 3rd parties and configure our platform Bot in it. The Bot will receive, end users’ queries and will then leverage the Assistant API (with Knowledge Retrieval tool, we’re adding a knowledge base file with Assistant for augmentation) before ‘asynchronously’ responding back to end user message.
Question: How to design a performant and scalable solution where our backend server will receive end user’s queries and it asynchronously passes it to Assistant API for responses - we’re looking for suggestions for how best to implement this polling mechanism since it seems we need to poll for every run separately.
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/703978 | Status Updates | API (2) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 704,268 | 2023-11-24T16:19:28.652Z | <p>Currently, the only way seem to be a manual polling:</p>
<ol>
<li>
<p>Put the promt/message from the end user on an exisitng or new thread (beware cost issues with extending the life of a Thread for too long) using <a href="https://platform.openai.com/docs/api-reference/messages/createMessage" rel="noopener nofollow ugc">https://platform.openai.com/docs/api-reference/messages/createMessage</a></p>
</li>
<li>
<p>Keep polling (<a href="https://platform.openai.com/docs/api-reference/runs/getRun" rel="noopener nofollow ugc">https://platform.openai.com/docs/api-reference/runs/getRun</a>) for the Run’s status to be one of the following: “requires_action”, “cancelled”, “failed”, “completed” or “expired”. You can set the polling iterval to something sensible (200ms-1000ms), depending on how much extra time you are willing to let your user wait. Responses typically take several seconds to generate anyway, so 1000ms polling interval should be fine. You can do all this in a separate thread, to avoid it blocking the end user.</p>
</li>
<li>
<p>Process the retrieved non-running Run</p>
</li>
</ol>
<p>3a) If status is “requires_action”, it wants you to run one or more tool (function). Apply the parameter payload to the functions it wants you to call, and return the results (<a href="https://platform.openai.com/docs/api-reference/runs/submitToolOutputs" rel="noopener nofollow ugc">https://platform.openai.com/docs/api-reference/runs/submitToolOutputs</a>) when all functions have been processed. This returns a new Run, process this (previous step). This could possible lead to recursive calls to your function that processes Runs.</p>
<p>3b) If status is “completed”, retrieve the latest (messages) from the thread and present to the user. You can utilize the before and after parameters and comparing the times in the Message objects to determine which messages to ask for (eg. what to show to the end-user, as the list of messages will also contain previous shown messages).</p>
<p>3c) Handle statuses “cancelled”, “failed” and “expired” by giving proper feedback to your end-user.</p>
<p>If it is too costly to create new threads for each end-user, you can have one separate poller-thread (or a thread-pool) where you submit each Run to, and it takes care of the polling. It can provide the list of messages back to the main thread when completed, in the same way as the “one thread per user” implementation does.</p>
<p>But yeah, webhooks would be a better solution…</p> | 84 | 2 | 0709b4cd61 | 12 | [
478937,
499916,
578711,
542300,
502525
] | null | Currently, the only way seem to be a manual polling:
1. Put the promt/message from the end user on an exisitng or new thread (beware cost issues with extending the life of a Thread for too long) using <https://platform.openai.com/docs/api-reference/messages/createMessage>
2. Keep polling (<https://platform.openai.com/docs/api-reference/runs/getRun>) for the Run’s status to be one of the following: “requires\_action”, “cancelled”, “failed”, “completed” or “expired”. You can set the polling iterval to something sensible (200ms-1000ms), depending on how much extra time you are willing to let your user wait. Responses typically take several seconds to generate anyway, so 1000ms polling interval should be fine. You can do all this in a separate thread, to avoid it blocking the end user.
3. Process the retrieved non-running Run
3a) If status is “requires\_action”, it wants you to run one or more tool (function). Apply the parameter payload to the functions it wants you to call, and return the results (<https://platform.openai.com/docs/api-reference/runs/submitToolOutputs>) when all functions have been processed. This returns a new Run, process this (previous step). This could possible lead to recursive calls to your function that processes Runs.
3b) If status is “completed”, retrieve the latest (messages) from the thread and present to the user. You can utilize the before and after parameters and comparing the times in the Message objects to determine which messages to ask for (eg. what to show to the end-user, as the list of messages will also contain previous shown messages).
3c) Handle statuses “cancelled”, “failed” and “expired” by giving proper feedback to your end-user.
If it is too costly to create new threads for each end-user, you can have one separate poller-thread (or a thread-pool) where you submit each Run to, and it takes care of the polling. It can provide the list of messages back to the main thread when completed, in the same way as the “one thread per user” implementation does.
But yeah, webhooks would be a better solution…
| api | neutral | 0.823317 | [
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/704268 | Threads (2) | Embeddings (6) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 705,411 | 2023-11-25T06:45:51.782Z | <p>thanks <a class="mention" href="/u/kristianv">@kristianv</a> for your suggestions! Yeah, looking forward to the webhook release!</p> | 75 | 0 | 8460448b05 | 13 | [
478937,
499916,
578711,
542300,
502525
] | null | thanks [@kristianv](/u/kristianv) for your suggestions! Yeah, looking forward to the webhook release!
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/705411 | Emoji (5) | Emoji (8) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 705,512 | 2023-11-25T08:28:34.530Z | <p>i don’t think pooling works like this. i could be wrong. the Run will ‘run’ depending on server side resources - the Assistant will add the (pooled) message or messages to the thread one at a time depending on the existing User messages in the thread. Once the assistant has finished the evaluation of the thread, the Run is set to ‘completed’. I only ever get multiple Assistant messages per Run if I the Assistant decided to use code interpreter.</p> | 71 | 0 | 266d0858c0 | 14 | [
478937,
499916,
578711,
542300,
502525
] | null | i don’t think pooling works like this. i could be wrong. the Run will ‘run’ depending on server side resources - the Assistant will add the (pooled) message or messages to the thread one at a time depending on the existing User messages in the thread. Once the assistant has finished the evaluation of the thread, the Run is set to ‘completed’. I only ever get multiple Assistant messages per Run if I the Assistant decided to use code interpreter.
| api | neutral | 0.701237 | [
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/705512 | Threads | Embeddings (6) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 705,524 | 2023-11-25T08:37:09.806Z | <p>you don’t create a new Run after updating the run with tool output when status = ‘requires_action’. You use the same run_id from previous step.</p>
<p>run = client.beta.threads.runs.submit_tool_outputs(<br>
thread_id=thread.id,<br>
<strong>run_id=run.id,</strong><br>
tool_outputs=[<br>
{<br>
“tool_call_id”: tool_call[0].id,<br>
“output”: <br>
}<br>
]<br>
)</p> | 71 | 0 | 266d0858c0 | 15 | [
478937,
499916,
578711,
542300,
502525
] | null | you don’t create a new Run after updating the run with tool output when status = ‘requires\_action’. You use the same run\_id from previous step.
run = client.beta.threads.runs.submit\_tool\_outputs(
thread\_id=thread.id,
**run\_id=run.id,**
tool\_outputs=[
{
“tool\_call\_id”: tool\_call[0].id,
“output”:
}
]
)
| api | neutral | 0.879304 | [
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/705524 | Status Updates | API (2) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 769,519 | 2023-12-23T12:57:34.665Z | <p>Perhaps using websocket or http2 sse (Server Sent Event) would be more appropriate</p> | 41 | 0 | 26faa38fbf | 16 | [
478937,
499916,
578711,
542300,
502525
] | null | Perhaps using websocket or http2 sse (Server Sent Event) would be more appropriate
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/769519 | Cloud Hosting | Payment (4) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 821,837 | 2024-01-26T23:43:17.152Z | <p>That’s exactly what I was thinking!! Everything would be smoother with a webhook! <img src="https://emoji.discourse-cdn.com/twitter/slight_smile.png?v=12" title=":slight_smile:" class="emoji" alt=":slight_smile:" loading="lazy" width="20" height="20"></p> | 24 | 0 | 6d5b834e86 | 17 | [
478937,
499916,
578711,
542300,
502525
] | null | That’s exactly what I was thinking!! Everything would be smoother with a webhook! 
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/821837 | Emoji, Twitter, PNG, Discourse, Heartbeat | Emoji (8) |
484,418 | [] | Assistants API run needs webhook | "2023-11-08T17:06:09.339000Z" | 7 | 2,853 | 10 | 17 | 10 | 1,347 | 894,769 | 2024-02-26T17:01:01.677Z | <p>I can’t wait for webhooks to be implemented for that. As an intermediate remedium for this all the polling stuff, I wrote a small library that does polling on OpenAI Threads API, so I don’t need to rewrite this code each time I use Assistants API. It’s on npm already and it’s called <span class="mention">@tmlc</span>/openai-polling</p> | 6 | 0 | 4199ddf401 | 18 | [
478937,
499916,
578711,
542300,
502525
] | null | I can’t wait for webhooks to be implemented for that. As an intermediate remedium for this all the polling stuff, I wrote a small library that does polling on OpenAI Threads API, so I don’t need to rewrite this code each time I use Assistants API. It’s on npm already and it’s called @tmlc/openai-polling
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] | null | null | null | null | https://community.openai.com/t/484418 | https://community.openai.com/p/894769 | PHP Libraries | Miscellaneous (27) |
647,518 | [
"api"
] | Easiest way to implement an Assistants API chatbot? | "2024-02-22T07:39:48.530000Z" | 7 | 121 | 0 | 0 | 3 | 203 | 884,217 | 2024-02-22T07:39:48.611Z | <p>I’d like to implement a simple chatbot to demonstrate a service to a client.</p>
<p>It’s like a custom GPTs.<br>
I tested it via GPTs and it works well.<br>
I input the custom instruction and domain knowledge files into the GPTs.</p>
<p>But I do not want to reveal ChatGPT user interface, because my service is not OpenAI’s.<br>
So, I’d like to show a simple chatbot with my logo.</p>
<p>Where can I build the chatbot as easy as possible?<br>
I am looking for a service that provides server, url and chat interface.<br>
And to put the domain knowledge files and the custom instruction, I want to use Assistant API.</p> | 23 | 0 | 0899048752 | 1 | [
566619,
577614,
601821,
589076,
561596
] | null | I’d like to implement a simple chatbot to demonstrate a service to a client.
It’s like a custom GPTs.
I tested it via GPTs and it works well.
I input the custom instruction and domain knowledge files into the GPTs.
But I do not want to reveal ChatGPT user interface, because my service is not OpenAI’s.
So, I’d like to show a simple chatbot with my logo.
Where can I build the chatbot as easy as possible?
I am looking for a service that provides server, url and chat interface.
And to put the domain knowledge files and the custom instruction, I want to use Assistant API.
| api | neutral | 0.540306 | [
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] | api | null | null | null | https://community.openai.com/t/647518 | https://community.openai.com/p/884217 | Miscellaneous (4) | GPTs (4) |
647,518 | [
"api"
] | Easiest way to implement an Assistants API chatbot? | "2024-02-22T07:39:48.530000Z" | 7 | 121 | 0 | 0 | 3 | 203 | 894,655 | 2024-02-26T15:59:50.351Z | <p>Hello,</p>
<p>I think if you want to build a custom interface would be to build your own website in nextjs and use vercel/ai sdk.</p>
<p>I know a SaaS that can do almost everything for you and it is called <a href="https://www.openassistantgpt.io/" rel="noopener nofollow ugc">OpenAssistantGPT</a>. With this app you can build a custom chatbot with the Assistant API.</p>
<p>If you have any question you can ask me I would be happy to help!</p> | 9 | 0 | e9544587ba | 2 | [
566619,
577614,
601821,
589076,
561596
] | null | Hello,
I think if you want to build a custom interface would be to build your own website in nextjs and use vercel/ai sdk.
I know a SaaS that can do almost everything for you and it is called [OpenAssistantGPT](https://www.openassistantgpt.io/). With this app you can build a custom chatbot with the Assistant API.
If you have any question you can ask me I would be happy to help!
| api | positive | 0.509942 | [
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] | api | null | null | null | https://community.openai.com/t/647518 | https://community.openai.com/p/894655 | Miscellaneous (4) | GPTs (4) |
647,518 | [
"api"
] | Easiest way to implement an Assistants API chatbot? | "2024-02-22T07:39:48.530000Z" | 7 | 121 | 0 | 0 | 3 | 203 | 894,700 | 2024-02-26T16:26:00.934Z | <p>Are you looking for this to be a web interface or an app? Do you have any coding experience?</p> | 6 | 0 | 6f019b1cf4 | 3 | [
566619,
577614,
601821,
589076,
561596
] | null | Are you looking for this to be a web interface or an app? Do you have any coding experience?
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] | api | null | null | null | https://community.openai.com/t/647518 | https://community.openai.com/p/894700 | Programming | Embeddings (6) |
655,548 | [
"chatgpt"
] | Needing Help with API Usage Error | "2024-02-26T16:15:43.424000Z" | 7 | 46 | 0 | 0 | 1 | 4 | 894,682 | 2024-02-26T16:15:43.493Z | <p>(topic deleted by author)</p> | 12 | 0 | e2dc877d75 | 1 | [
180159,
574478,
33471,
386831,
585747
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] | chatgpt | null | null | null | https://community.openai.com/t/655548 | https://community.openai.com/p/894682 | Moderation | Emoji (8) |
655,360 | [
"api",
"gpt-35-turbo",
"streaming"
] | How to handle token rate limit while streaming the response | "2024-02-26T14:21:05.329000Z" | 7 | 51 | 0 | 0 | 2 | 181 | 894,451 | 2024-02-26T14:21:05.394Z | <p>I want to use opaniAI api for a production system wherein i want to stream the response for the user. There is a possibility that the token rate limit might exceed while the response is being streamed to the user. In such a case, the user will only get to see half the response which is bad in terms of user interaction. Is there a way to handle this?? maybe by predicting the tokens that the model will generate or by getting the token rate limit error before the stream starts and not in the middle so that i can send the request to another instance of the LLM.</p> | 9 | 0 | 62f90d6fdb | 1 | [
263245,
226957,
655067,
593552,
467133
] | null | I want to use opaniAI api for a production system wherein i want to stream the response for the user. There is a possibility that the token rate limit might exceed while the response is being streamed to the user. In such a case, the user will only get to see half the response which is bad in terms of user interaction. Is there a way to handle this?? maybe by predicting the tokens that the model will generate or by getting the token rate limit error before the stream starts and not in the middle so that i can send the request to another instance of the LLM.
| api | neutral | 0.573531 | [
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] | api | gpt-35-turbo | streaming | null | https://community.openai.com/t/655360 | https://community.openai.com/p/894451 | TPM, RPM, Ratelimit | Tokenization (2) |
655,360 | [
"api",
"gpt-35-turbo",
"streaming"
] | How to handle token rate limit while streaming the response | "2024-02-26T14:21:05.329000Z" | 7 | 51 | 0 | 0 | 2 | 181 | 894,664 | 2024-02-26T16:07:25.568Z | <p>Hi <a class="mention" href="/u/palashmunshi">@palashmunshi</a> and welcome to the Forum.</p>
<p>One way to think about this problem is to ensure that you input tokens do not exceed a certain threshold, leaving always enough room for the max output tokens you are expecting to generate.</p>
<p>At the most, you are looking at 4096 output tokens - although in practice this number will typically be significantly lower. You can further control your output tokens via the max_output hyperparameter.</p> | 8 | 0 | 5b48a0acbf | 2 | [
263245,
226957,
655067,
593552,
467133
] | null | Hi [@palashmunshi](/u/palashmunshi) and welcome to the Forum.
One way to think about this problem is to ensure that you input tokens do not exceed a certain threshold, leaving always enough room for the max output tokens you are expecting to generate.
At the most, you are looking at 4096 output tokens - although in practice this number will typically be significantly lower. You can further control your output tokens via the max\_output hyperparameter.
| api | neutral | 0.718345 | [
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] | api | gpt-35-turbo | streaming | null | https://community.openai.com/t/655360 | https://community.openai.com/p/894664 | Booking | Tokenization (2) |
575,807 | [
"langchain"
] | What do you think about langchain? | "2023-12-30T06:16:28.004000Z" | 7 | 2,739 | 6 | 11 | 8 | 997 | 778,763 | 2023-12-30T06:16:28.064Z | <p>There were posts about the langchain library in this forum earlier, but it hasn’t been mentioned so much recently.</p>
<p>Are you using it? Is it good? Is it still relevant? Has another standard surpassed it?</p> | 113 | 1 | 8ade7cb075 | 1 | [
228923,
163139,
589772,
342730,
554930
] | null | There were posts about the langchain library in this forum earlier, but it hasn’t been mentioned so much recently.
Are you using it? Is it good? Is it still relevant? Has another standard surpassed it?
| api | neutral | 0.827441 | [
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] | langchain | null | null | null | https://community.openai.com/t/575807 | https://community.openai.com/p/778763 | Languages | Artificial Intelligence |
575,807 | [
"langchain"
] | What do you think about langchain? | "2023-12-30T06:16:28.004000Z" | 7 | 2,739 | 6 | 11 | 8 | 997 | 778,768 | 2023-12-30T06:18:34.430Z | <p>I used to use it a lot, but stopped. Don’t see much value compared to doing the same oneself.</p>
<p>But it is definitely great for newcomers as quick start in using LLM’s</p> | 113 | 0 | 5d441d94a5 | 2 | [
228923,
163139,
589772,
342730,
554930
] | null | I used to use it a lot, but stopped. Don’t see much value compared to doing the same oneself.
But it is definitely great for newcomers as quick start in using LLM’s
| api | positive | 0.570906 | [
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] | langchain | null | null | null | https://community.openai.com/t/575807 | https://community.openai.com/p/778768 | LLMs | Artificial Intelligence |
575,807 | [
"langchain"
] | What do you think about langchain? | "2023-12-30T06:16:28.004000Z" | 7 | 2,739 | 6 | 11 | 8 | 997 | 778,814 | 2023-12-30T07:03:30.157Z | <p>Only use it when I develop with local LLM.</p> | 107 | 1 | cc5af3faac | 3 | [
228923,
163139,
589772,
342730,
554930
] | null | Only use it when I develop with local LLM.
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] | langchain | null | null | null | https://community.openai.com/t/575807 | https://community.openai.com/p/778814 | LLMs | Artificial Intelligence |
575,807 | [
"langchain"
] | What do you think about langchain? | "2023-12-30T06:16:28.004000Z" | 7 | 2,739 | 6 | 11 | 8 | 997 | 778,819 | 2023-12-30T07:06:52.028Z | <p>Thanks for responding. Why only local?</p> | 104 | 1 | 8ade7cb075 | 4 | [
228923,
163139,
589772,
342730,
554930
] | null | Thanks for responding. Why only local?
| api | neutral | 0.50044 | [
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] | langchain | null | null | null | https://community.openai.com/t/575807 | https://community.openai.com/p/778819 | Women's Feedback | Emoji (8) |
575,807 | [
"langchain"
] | What do you think about langchain? | "2023-12-30T06:16:28.004000Z" | 7 | 2,739 | 6 | 11 | 8 | 997 | 778,832 | 2023-12-30T07:16:09.519Z | <p><a href="https://github.com/openai/openai-python" rel="noopener nofollow ugc">openai-python</a> is already sufficient for development if my application is calling OpenAI’s endpoint.</p> | 99 | 1 | cc5af3faac | 5 | [
228923,
163139,
589772,
342730,
554930
] | null | [openai-python](https://github.com/openai/openai-python) is already sufficient for development if my application is calling OpenAI’s endpoint.
| api | positive | 0.677762 | [
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] | langchain | null | null | null | https://community.openai.com/t/575807 | https://community.openai.com/p/778832 | OpenAI | Miscellaneous (27) |
575,807 | [
"langchain"
] | What do you think about langchain? | "2023-12-30T06:16:28.004000Z" | 7 | 2,739 | 6 | 11 | 8 | 997 | 778,915 | 2023-12-30T08:32:43.088Z | <p>If you were using other sources as well (Not just OpenAI), would you consider using LangChain, or do you think Langchain has nothing to offer?</p> | 89 | 2 | 8ade7cb075 | 6 | [
228923,
163139,
589772,
342730,
554930
] | null | If you were using other sources as well (Not just OpenAI), would you consider using LangChain, or do you think Langchain has nothing to offer?
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] | langchain | null | null | null | https://community.openai.com/t/575807 | https://community.openai.com/p/778915 | PHP Libraries | Miscellaneous (27) |
575,807 | [
"langchain"
] | What do you think about langchain? | "2023-12-30T06:16:28.004000Z" | 7 | 2,739 | 6 | 11 | 8 | 997 | 779,027 | 2023-12-30T11:37:38.755Z | <p>I am someone who is using multiple LLMs from multiple providers on a platform I wrote in PHP. I began my AI journey at the beginning of this year, but I came with some 20+ years of PHP programming experience. So I’m thinking, “Why do I have to learn another programming language in order to do development with LLMs, all of which have documented APIs?” Best decision ever.</p>
<p>That said, if you don’t have an extensive programming background and want to get into this game, I don’t see a better way than Langchain, with it’s huge Python library.</p> | 86 | 0 | 9716394c2d | 7 | [
228923,
163139,
589772,
342730,
554930
] | null | I am someone who is using multiple LLMs from multiple providers on a platform I wrote in PHP. I began my AI journey at the beginning of this year, but I came with some 20+ years of PHP programming experience. So I’m thinking, “Why do I have to learn another programming language in order to do development with LLMs, all of which have documented APIs?” Best decision ever.
That said, if you don’t have an extensive programming background and want to get into this game, I don’t see a better way than Langchain, with it’s huge Python library.
| api | positive | 0.765943 | [
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] | langchain | null | null | null | https://community.openai.com/t/575807 | https://community.openai.com/p/779027 | LLMs | Artificial Intelligence |
575,807 | [
"langchain"
] | What do you think about langchain? | "2023-12-30T06:16:28.004000Z" | 7 | 2,739 | 6 | 11 | 8 | 997 | 780,142 | 2023-12-31T05:30:09.787Z | <p>For me the biggest problem (again, not rejecting all its benefits) was that it’s a high level abstraction which in many case you don’t have control of. In many cases langchain uses its own system prompts that make the stochastic parrot even more stochastic as it adds another layer of uncertainty (and a lot of time wasted figuring out why your prompts don’t work as expected).</p> | 75 | 0 | 5d441d94a5 | 8 | [
228923,
163139,
589772,
342730,
554930
] | null | For me the biggest problem (again, not rejecting all its benefits) was that it’s a high level abstraction which in many case you don’t have control of. In many cases langchain uses its own system prompts that make the stochastic parrot even more stochastic as it adds another layer of uncertainty (and a lot of time wasted figuring out why your prompts don’t work as expected).
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] | langchain | null | null | null | https://community.openai.com/t/575807 | https://community.openai.com/p/780142 | Sampling | Artificial Intelligence |
575,807 | [
"langchain"
] | What do you think about langchain? | "2023-12-30T06:16:28.004000Z" | 7 | 2,739 | 6 | 11 | 8 | 997 | 780,494 | 2023-12-31T12:19:38.596Z | <aside class="quote no-group" data-username="Man" data-post="1" data-topic="575807">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/man/48/265780_2.png" class="avatar"> Man:</div>
<blockquote>
<p>There were posts about the langchain library in this forum earlier, but it hasn’t been mentioned so much recently.</p>
</blockquote>
</aside>
<p>Without specific dates, it’s challenging to visualize the timeline you have in mind.</p>
<p>A few months ago, most notably OpenAI DevDay (Nov 6, 2023), OpenAI added new functionality to both the API such as <a href="https://platform.openai.com/docs/assistants/overview">assistants</a> and to ChatGPT such as <a href="https://openai.com/blog/introducing-gpts">custom GPTs</a>.</p>
<aside class="onebox allowlistedgeneric" data-onebox-src="https://openai.com/blog/new-models-and-developer-products-announced-at-devday">
<header class="source">
<a href="https://openai.com/blog/new-models-and-developer-products-announced-at-devday" target="_blank" rel="noopener">openai.com</a>
</header>
<article class="onebox-body">
<img width="500" height="500" src="https://global.discourse-cdn.com/openai1/optimized/3X/a/9/a935d5a97cb27df946aa24c608e6d0168f868682_2_500x500.jpeg" class="thumbnail onebox-avatar" data-dominant-color="EEEBE9">
<h3><a href="https://openai.com/blog/new-models-and-developer-products-announced-at-devday" target="_blank" rel="noopener">New models and developer products announced at DevDay</a></h3>
<p>GPT-4 Turbo with 128K context and lower prices, the new Assistants API, GPT-4 Turbo with Vision, DALL·E 3 API, and more.</p>
</article>
<div class="onebox-metadata">
</div>
<div style="clear: both"></div>
</aside>
<p>As a result, the discussion topics seem to have shifted towards users experimenting with these new products in comparison to similar offerings like <a href="https://python.langchain.com/docs/get_started/introduction">LangChain</a>.</p> | 70 | 1 | 53ef158388 | 9 | [
228923,
163139,
589772,
342730,
554930
] | null |
 Man:
>
> There were posts about the langchain library in this forum earlier, but it hasn’t been mentioned so much recently.
>
>
>
Without specific dates, it’s challenging to visualize the timeline you have in mind.
A few months ago, most notably OpenAI DevDay (Nov 6, 2023), OpenAI added new functionality to both the API such as [assistants](https://platform.openai.com/docs/assistants/overview) and to ChatGPT such as [custom GPTs](https://openai.com/blog/introducing-gpts).
[openai.com](https://openai.com/blog/new-models-and-developer-products-announced-at-devday)
### [New models and developer products announced at DevDay](https://openai.com/blog/new-models-and-developer-products-announced-at-devday)
GPT-4 Turbo with 128K context and lower prices, the new Assistants API, GPT-4 Turbo with Vision, DALL·E 3 API, and more.
As a result, the discussion topics seem to have shifted towards users experimenting with these new products in comparison to similar offerings like [LangChain](https://python.langchain.com/docs/get_started/introduction).
| api | neutral | 0.875839 | [
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] | langchain | null | null | null | https://community.openai.com/t/575807 | https://community.openai.com/p/780494 | Miscellaneous (26) | GPTs (4) |
575,807 | [
"langchain"
] | What do you think about langchain? | "2023-12-30T06:16:28.004000Z" | 7 | 2,739 | 6 | 11 | 8 | 997 | 780,523 | 2023-12-31T12:52:19.443Z | <aside class="quote no-group" data-username="EricGT" data-post="9" data-topic="575807">
<div class="title">
<div class="quote-controls"></div>
<img loading="lazy" alt="" width="24" height="24" src="https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/ericgt/48/20571_2.png" class="avatar"> EricGT:</div>
<blockquote>
<p>Without specific dates, it’s challenging to visualize the timeline you have in mind.</p>
</blockquote>
</aside>
<p>Ya. It’s hard to discuss. I suppose even ChatGPT can’t hold a good discussion with just<br>
“What do you think about langchain?”</p> | 64 | 0 | cc5af3faac | 10 | [
228923,
163139,
589772,
342730,
554930
] | null |
 EricGT:
>
> Without specific dates, it’s challenging to visualize the timeline you have in mind.
>
>
>
Ya. It’s hard to discuss. I suppose even ChatGPT can’t hold a good discussion with just
“What do you think about langchain?”
| api | neutral | 0.700675 | [
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] | langchain | null | null | null | https://community.openai.com/t/575807 | https://community.openai.com/p/780523 | Miscellaneous (5) | Miscellaneous (27) |
575,807 | [
"langchain"
] | What do you think about langchain? | "2023-12-30T06:16:28.004000Z" | 7 | 2,739 | 6 | 11 | 8 | 997 | 780,624 | 2023-12-31T14:47:09.696Z | <p>Here’s a recent discussion (one of many) responding to a question about using LangChain in production, in the r/LocalLLama forum: <a href="https://www.reddit.com/r/LocalLLaMA/comments/18v0sxq/is_anyone_actually_using_langchain_in_production/" class="inline-onebox" rel="noopener nofollow ugc">Reddit - Dive into anything</a></p>
<p>Since you asked about possible alternatives, I’ll mention Langroid (a couple of commenters in the above thread mention switching to Langroid from LangChain).</p>
<p>We have a few companies using Langroid in production (contact center management, document-vs-spec matching/scoring) after evaluating others including LC and AutoGen. Langroid is a multi-agent LLM framework from ex-CMU and UW Madison researchers: <a href="https://github.com/langroid/langroid" class="inline-onebox" rel="noopener nofollow ugc">GitHub - langroid/langroid: Harness LLMs with Multi-Agent Programming</a>.<br>
[To be clear, it does not use LangChain].</p>
<p>We expressly designed this framework to simplify building applications, using an agent-oriented approach from the start. You can define agents with optional tools and vector-db, assign them tasks, and have them collaborate via messages: this is a “conversational programming” paradigm. It works with local/open and remote/proprietary LLMs.</p>
<p>A MultiAgent approach often leads to simpler solutions compared to stuffing too much into a single agent. Langroid has a built-in task orchestrator that seamlessly works for LLM tool/function handling (with retries when LLM deviates), as well as sub-task handoff.</p>
<p>We’ve avoided bloat and excessive abstractions to keep the framework light, stable, and easy to tweak — e.g all of the RAG capabilities are in a single DocChatAgent class, and code written 5 months ago still works. Granted our documentation is lagging behind our features, but there are plenty of tests and examples clarifying usage.</p>
<p>I’ve been personally super-productive building complex multi-agent workflows using this framework for a couple of clients. The demands of these client projects drive feature development in Langroid.</p>
<p>Here’s a Colab quick-start that builds up to a 2-agent system to extract structured info from a document:</p>
<aside class="onebox allowlistedgeneric" data-onebox-src="https://colab.research.google.com/github/langroid/langroid/blob/main/examples/Langroid_quick_start.ipynb">
<header class="source">
<img src="https://global.discourse-cdn.com/openai1/original/4X/4/a/f/4af0646ef4b38e2bc72dd9b49a8edbcd1ee7803d.png" class="site-icon" data-dominant-color="F29404" width="16" height="16">
<a href="https://colab.research.google.com/github/langroid/langroid/blob/main/examples/Langroid_quick_start.ipynb" target="_blank" rel="noopener nofollow ugc">colab.research.google.com</a>
</header>
<article class="onebox-body">
<img width="260" height="260" src="https://global.discourse-cdn.com/openai1/original/3X/5/b/5b77e9737d5f8f8bc5f7b35e7fc0f8088fd1ebd8.png" class="thumbnail onebox-avatar" data-dominant-color="F29304">
<h3><a href="https://colab.research.google.com/github/langroid/langroid/blob/main/examples/Langroid_quick_start.ipynb" target="_blank" rel="noopener nofollow ugc">Google Colaboratory</a></h3>
</article>
<div class="onebox-metadata">
</div>
<div style="clear: both"></div>
</aside>
| 61 | 0 | 61aef9df1a | 11 | [
228923,
163139,
589772,
342730,
554930
] | null | Here’s a recent discussion (one of many) responding to a question about using LangChain in production, in the r/LocalLLama forum: [Reddit - Dive into anything](https://www.reddit.com/r/LocalLLaMA/comments/18v0sxq/is_anyone_actually_using_langchain_in_production/)
Since you asked about possible alternatives, I’ll mention Langroid (a couple of commenters in the above thread mention switching to Langroid from LangChain).
We have a few companies using Langroid in production (contact center management, document-vs-spec matching/scoring) after evaluating others including LC and AutoGen. Langroid is a multi-agent LLM framework from ex-CMU and UW Madison researchers: [GitHub - langroid/langroid: Harness LLMs with Multi-Agent Programming](https://github.com/langroid/langroid).
[To be clear, it does not use LangChain].
We expressly designed this framework to simplify building applications, using an agent-oriented approach from the start. You can define agents with optional tools and vector-db, assign them tasks, and have them collaborate via messages: this is a “conversational programming” paradigm. It works with local/open and remote/proprietary LLMs.
A MultiAgent approach often leads to simpler solutions compared to stuffing too much into a single agent. Langroid has a built-in task orchestrator that seamlessly works for LLM tool/function handling (with retries when LLM deviates), as well as sub-task handoff.
We’ve avoided bloat and excessive abstractions to keep the framework light, stable, and easy to tweak — e.g all of the RAG capabilities are in a single DocChatAgent class, and code written 5 months ago still works. Granted our documentation is lagging behind our features, but there are plenty of tests and examples clarifying usage.
I’ve been personally super-productive building complex multi-agent workflows using this framework for a couple of clients. The demands of these client projects drive feature development in Langroid.
Here’s a Colab quick-start that builds up to a 2-agent system to extract structured info from a document:
[colab.research.google.com](https://colab.research.google.com/github/langroid/langroid/blob/main/examples/Langroid_quick_start.ipynb)
### [Google Colaboratory](https://colab.research.google.com/github/langroid/langroid/blob/main/examples/Langroid_quick_start.ipynb)
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] | langchain | null | null | null | https://community.openai.com/t/575807 | https://community.openai.com/p/780624 | LLMs | Artificial Intelligence |
575,807 | [
"langchain"
] | What do you think about langchain? | "2023-12-30T06:16:28.004000Z" | 7 | 2,739 | 6 | 11 | 8 | 997 | 781,253 | 2024-01-01T02:06:21.723Z | <p>I agree with most of the comments here, langchain is good when you’re getting started. Doc isn’t great but has enough breadcrumbs if you’re willing to get into the source code. Prompts are key and you can pull from them as “starter templates”. The model abstraction was appealing to me at the beginning but you need to adjust prompts based on different models so that becomes a little tedious.</p>
<p>The vector database and memory abstraction is useful but takes some langchain specific memory management understanding to make sure the memory follows you.</p>
<p>For example I was using local memory then easily swapped it out for an open source solution, zep (<a href="http://getzep.com" rel="noopener nofollow ugc">getzep.com</a>) for persistent memory. Also swapping vector databases and other tools is pretty easy.</p>
<p>If you’re new to AI development trolling the document and seeing what tools are out there was really helpful.</p> | 47 | 0 | 448b4de3bc | 12 | [
228923,
163139,
589772,
342730,
554930
] | null | I agree with most of the comments here, langchain is good when you’re getting started. Doc isn’t great but has enough breadcrumbs if you’re willing to get into the source code. Prompts are key and you can pull from them as “starter templates”. The model abstraction was appealing to me at the beginning but you need to adjust prompts based on different models so that becomes a little tedious.
The vector database and memory abstraction is useful but takes some langchain specific memory management understanding to make sure the memory follows you.
For example I was using local memory then easily swapped it out for an open source solution, zep ([getzep.com](http://getzep.com)) for persistent memory. Also swapping vector databases and other tools is pretty easy.
If you’re new to AI development trolling the document and seeing what tools are out there was really helpful.
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] | langchain | null | null | null | https://community.openai.com/t/575807 | https://community.openai.com/p/781253 | Writing Prompts | Artificial Intelligence |
575,807 | [
"langchain"
] | What do you think about langchain? | "2023-12-30T06:16:28.004000Z" | 7 | 2,739 | 6 | 11 | 8 | 997 | 894,652 | 2024-02-26T15:59:10.540Z | <p>I found it much better not to use LangChain for my projects. Without LangChain, my model is much faster, you have access to everything, and you know perfectly how everything works behind the scenes. I think it’s great for starting to learn, but it’s not the most convenient for turning it into a product.</p> | 5 | 0 | 331db3b7ae | 13 | [
228923,
163139,
589772,
342730,
554930
] | null | I found it much better not to use LangChain for my projects. Without LangChain, my model is much faster, you have access to everything, and you know perfectly how everything works behind the scenes. I think it’s great for starting to learn, but it’s not the most convenient for turning it into a product.
| api | neutral | 0.455757 | [
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] | langchain | null | null | null | https://community.openai.com/t/575807 | https://community.openai.com/p/894652 | LLMs | Artificial Intelligence |
655,516 | [] | Getting error {"detail":"openai error: Please submit an `input`."} | "2024-02-26T15:53:53.271000Z" | 7 | 38 | 0 | 0 | 1 | 78 | 894,637 | 2024-02-26T15:53:53.330Z | <p>I have integrated gptcache in a server application.<br>
on calling below method ,<br>
openai_response = openai.ChatCompletion.create(<br>
cache_obj=openai_cache,<br>
cache_skip=cache_skip,<br>
api_key=openai_key,<br>
**openai_params,<br>
)</p>
<p>with data,<br>
payload = {</p>
<pre><code> 'model': 'gpt-3.5-turbo',
'messages': [{"role": "system", "content": "You are a helpful assistant."},
{'role': 'user', 'content': user_question}]
}
</code></pre>
<p>am getting error:<br>
{“detail”:“openai error: Please submit an <code>input</code>.”}</p>
<p>The issue is seen when embedding model used for cache config is “openai”, when used model “ONNX”, able to get response from open ai.</p> | 8 | 0 | 8f1ad398c5 | 1 | [
319294,
137681,
80668,
194035,
608954
] | null | I have integrated gptcache in a server application.
on calling below method ,
openai\_response = openai.ChatCompletion.create(
cache\_obj=openai\_cache,
cache\_skip=cache\_skip,
api\_key=openai\_key,
\*\*openai\_params,
)
with data,
payload = {
```
'model': 'gpt-3.5-turbo',
'messages': [{"role": "system", "content": "You are a helpful assistant."},
{'role': 'user', 'content': user_question}]
}
```
am getting error:
{“detail”:“openai error: Please submit an `input`.”}
The issue is seen when embedding model used for cache config is “openai”, when used model “ONNX”, able to get response from open ai.
| api | neutral | 0.850899 | [
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] | null | null | null | null | https://community.openai.com/t/655516 | https://community.openai.com/p/894637 | Assistant | Miscellaneous (27) |
655,502 | [
"api"
] | Links in streamed responses | "2024-02-26T15:49:00.977000Z" | 7 | 37 | 0 | 0 | 1 | 118 | 894,622 | 2024-02-26T15:49:01.074Z | <p>I am receiving a streamed response by OpenAi, which works wonderfully (Answer is generated in PHP, then appended in html with javascript).</p>
<p>The big issue I have is, if the response contains a link using the format <a></a>, where the text is between the brackets and the link between the parenthesis, the answer comes back bits by bits with the “pre-formatted” answer and is shown to the user, until the link is complete and is correctly shown.</p>
<p>Is there anyway to receive links “all” at once instead of bits by bits for the streamed response ? Currently, I can have scenarii where the chunks are “[”,“Google]”,“(http”, etc. which is hard to detect as the format can be random.</p> | 8 | 0 | 0db30b1bd0 | 1 | [
315289,
90961,
321813,
256791,
347488
] | null | I am receiving a streamed response by OpenAi, which works wonderfully (Answer is generated in PHP, then appended in html with javascript).
The big issue I have is, if the response contains a link using the format , where the text is between the brackets and the link between the parenthesis, the answer comes back bits by bits with the “pre-formatted” answer and is shown to the user, until the link is complete and is correctly shown.
Is there anyway to receive links “all” at once instead of bits by bits for the streamed response ? Currently, I can have scenarii where the chunks are “[”,“Google]”,“(http”, etc. which is hard to detect as the format can be random.
| api | positive | 0.751874 | [
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] | api | null | null | null | https://community.openai.com/t/655502 | https://community.openai.com/p/894622 | AI Assistants | Embeddings (6) |
655,501 | [
"tts"
] | Difference between tts-1 and tts-1-1106 | "2024-02-26T15:48:41.662000Z" | 7 | 42 | 0 | 0 | 1 | 23 | 894,621 | 2024-02-26T15:48:41.730Z | <p>Hi, is there a difference between these two models in tts? I noticed these two under limits today.</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/d/5/4/d541ef08a84d2eb4673d23e6fc12c256edcbf12d.png" data-download-href="/uploads/short-url/uqyXJVKMhNRzJssN5vQ4DdN1ZcF.png?dl=1" title="image" rel="noopener nofollow ugc"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/d/5/4/d541ef08a84d2eb4673d23e6fc12c256edcbf12d_2_690x368.png" alt="image" data-base62-sha1="uqyXJVKMhNRzJssN5vQ4DdN1ZcF" width="690" height="368" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/d/5/4/d541ef08a84d2eb4673d23e6fc12c256edcbf12d_2_690x368.png, https://global.discourse-cdn.com/openai1/optimized/4X/d/5/4/d541ef08a84d2eb4673d23e6fc12c256edcbf12d_2_1035x552.png 1.5x, https://global.discourse-cdn.com/openai1/original/4X/d/5/4/d541ef08a84d2eb4673d23e6fc12c256edcbf12d.png 2x" data-dominant-color="FAFAF8"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">image</span><span class="informations">1165×622 32.6 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p> | 7 | 0 | fcdcf2dc68 | 1 | [
555910,
578537,
494438,
610302,
475394
] | null | Hi, is there a difference between these two models in tts? I noticed these two under limits today.
[image1165×622 32.6 KB](https://global.discourse-cdn.com/openai1/original/4X/d/5/4/d541ef08a84d2eb4673d23e6fc12c256edcbf12d.png "image")
| api | neutral | 0.733567 | [
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] | tts | null | null | null | https://community.openai.com/t/655501 | https://community.openai.com/p/894621 | Vehicle models | Payment (4) |
655,301 | [
"gpt-4",
"assistants-api",
"threads",
"api-threads"
] | I have several question Regarding GPT 3.5 or GPT 4, Thread, & Assistant | "2024-02-26T13:46:05.638000Z" | 7 | 78 | 0 | 0 | 2 | 1,321 | 894,378 | 2024-02-26T13:46:05.729Z | <p>I have several question that I want to make sure for this 3 section:</p>
<p><strong>First Section - GPT 3.5 - GPT 4</strong></p>
<ol>
<li>
<p>In the docs it state that new Model is from 2023 - ???, as for ??? how long the range it included? is it until our current date? let say if now this question created on Feb 26th, 2024, is it mean the model knowledge has 0 gap date which up to date to this exact date or how long the gap between the knowledge is provided? I tried to search on documentation but there is no exact statement about this, maybe can be helpful if you put some kind of statement in there, let say there is a new movie which release next week, can it get what the schedule and which cinema that release it?</p>
</li>
<li>
<p>Regarding streaming, Since we already know that Chat GPT itself using stream method to generate the answer, I’m curious regarding what is the biggest differences between using normal method & stream approach? is it make the right answer more precise than normal way, or is it make the cost more cheaper compared to the normal one with the benefit of fastest result? (Since I guess it’s somehow chunk the full context before returning it & in documentation only state iteratively and not touch any other reason for it so I’m curious about the advantage & disadvantage of both method)</p>
</li>
</ol>
<p><strong>Second Section - Thread</strong></p>
<ol>
<li>
<p>Is there any example as how thread response will be? I mean on documentation the response somehow from user perspective like<br>
<strong>How does AI work? Explain it in simple terms.</strong>, but I can’t find example from the open AI answer for this question and how the response looks like</p>
</li>
<li>
<p>Let say if I have 3 thread, thread A have a topic about music, thread B have a topic about fashion, and thread C have a topic about Hiking. is there any way for thread A to relate to the topic of thread C? like something I said on Thread C regarding Hiking and reference it to thread A or thread B? for example in Hiking I have a joke about the meaning of <strong>Huwawa which means camp without fire to counter bear</strong>, If I said <strong>“do you still remember about Huwawa? can you create a song about it”</strong> on thread A, can it still reference it? or is there any way I can achieve it? (or is it even not possible to have cross threads topic like this? like a limitation for threads?)</p>
</li>
<li>
<p>There is file id parameter on documentation, I want to make sure this case, is this file id in here if I use <strong>Code Interpreter</strong> means Open AI can know and train the context of the file itself? let say I upload PDF about a story, can it tell me what the conclusion of the story from the file that I upload using this parameter?</p>
</li>
<li>
<p>Is thread log have the same behavior as Chat where it will be removed after 30 days? if yes, can it still know what we talk before or should we consider the knowledge on that thread is gone?</p>
</li>
<li>
<p>Is token on the thread or main message will be count as the request token every time I send a new message on the thread? let say I make a rule on thread that it will always return in some kind of symbol, so on the 3rd message I will just write “Hello world” & the message will return a symbol right? is the first rule on the thread count as request token too for the N message after the first rule I state or it will be treat separately? (like rule cost 300 token while new request message count as 45 token, will it always sum it up into 345 token for the new message or will it stick to 45 token)</p>
</li>
</ol>
<p><strong>Third Section - Assistant</strong><br>
This is actually what is interesting in the new update and I have some kind of question about this</p>
<ol>
<li>
<p>Since Assistant have the same main behavior with thread (from my understanding) what the most noticable differences with the thread? since thread can use tools too like <strong>code interval & retrieval</strong> It make me hard to find the difference between this too</p>
</li>
<li>
<p>I believe I read it in the forum about assistant cost for token, it seems it count as free except for the <strong>code interval & retrieval</strong> which use session for cost, so if it correct (CMIIW), as long as we don’t send any tools (I mean file either upload or retrieve it), it have the same behavior as Thread and chat right?</p>
</li>
<li>
<p>last is about cost on using it, I think it will starting to charge the moment you call it (the tools), but as for let say using code retrieval it will only cost <strong>0.2</strong> for an hour, let say if now is 14:00, will it means it will charge me again on 15:01 or for the usage duration, means if I use it only half an hour, since I still have half hour left, I will not be charge for the next half hour if I use it again on 16:00-16:30?</p>
</li>
</ol>
<p>Thanks in advance, sorry if the questions is a lot, since I really excited to find how far Open AI can take my project to</p>
<p>Best Regards,<br>
Rakish</p> | 12 | 0 | bb343aa08f | 1 | [
575105,
497675,
534869,
523555,
573028
] | null | I have several question that I want to make sure for this 3 section:
**First Section - GPT 3.5 - GPT 4**
1. In the docs it state that new Model is from 2023 - ???, as for ??? how long the range it included? is it until our current date? let say if now this question created on Feb 26th, 2024, is it mean the model knowledge has 0 gap date which up to date to this exact date or how long the gap between the knowledge is provided? I tried to search on documentation but there is no exact statement about this, maybe can be helpful if you put some kind of statement in there, let say there is a new movie which release next week, can it get what the schedule and which cinema that release it?
2. Regarding streaming, Since we already know that Chat GPT itself using stream method to generate the answer, I’m curious regarding what is the biggest differences between using normal method & stream approach? is it make the right answer more precise than normal way, or is it make the cost more cheaper compared to the normal one with the benefit of fastest result? (Since I guess it’s somehow chunk the full context before returning it & in documentation only state iteratively and not touch any other reason for it so I’m curious about the advantage & disadvantage of both method)
**Second Section - Thread**
1. Is there any example as how thread response will be? I mean on documentation the response somehow from user perspective like
**How does AI work? Explain it in simple terms.**, but I can’t find example from the open AI answer for this question and how the response looks like
2. Let say if I have 3 thread, thread A have a topic about music, thread B have a topic about fashion, and thread C have a topic about Hiking. is there any way for thread A to relate to the topic of thread C? like something I said on Thread C regarding Hiking and reference it to thread A or thread B? for example in Hiking I have a joke about the meaning of **Huwawa which means camp without fire to counter bear**, If I said **“do you still remember about Huwawa? can you create a song about it”** on thread A, can it still reference it? or is there any way I can achieve it? (or is it even not possible to have cross threads topic like this? like a limitation for threads?)
3. There is file id parameter on documentation, I want to make sure this case, is this file id in here if I use **Code Interpreter** means Open AI can know and train the context of the file itself? let say I upload PDF about a story, can it tell me what the conclusion of the story from the file that I upload using this parameter?
4. Is thread log have the same behavior as Chat where it will be removed after 30 days? if yes, can it still know what we talk before or should we consider the knowledge on that thread is gone?
5. Is token on the thread or main message will be count as the request token every time I send a new message on the thread? let say I make a rule on thread that it will always return in some kind of symbol, so on the 3rd message I will just write “Hello world” & the message will return a symbol right? is the first rule on the thread count as request token too for the N message after the first rule I state or it will be treat separately? (like rule cost 300 token while new request message count as 45 token, will it always sum it up into 345 token for the new message or will it stick to 45 token)
**Third Section - Assistant**
This is actually what is interesting in the new update and I have some kind of question about this
1. Since Assistant have the same main behavior with thread (from my understanding) what the most noticable differences with the thread? since thread can use tools too like **code interval & retrieval** It make me hard to find the difference between this too
2. I believe I read it in the forum about assistant cost for token, it seems it count as free except for the **code interval & retrieval** which use session for cost, so if it correct (CMIIW), as long as we don’t send any tools (I mean file either upload or retrieve it), it have the same behavior as Thread and chat right?
3. last is about cost on using it, I think it will starting to charge the moment you call it (the tools), but as for let say using code retrieval it will only cost **0.2** for an hour, let say if now is 14:00, will it means it will charge me again on 15:01 or for the usage duration, means if I use it only half an hour, since I still have half hour left, I will not be charge for the next half hour if I use it again on 16:00-16:30?
Thanks in advance, sorry if the questions is a lot, since I really excited to find how far Open AI can take my project to
Best Regards,
Rakish
| api | neutral | 0.911507 | [
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] | gpt-4 | assistants-api | threads | api-threads | https://community.openai.com/t/655301 | https://community.openai.com/p/894378 | Dataset Training | GPTs (4) |
655,301 | [
"gpt-4",
"assistants-api",
"threads",
"api-threads"
] | I have several question Regarding GPT 3.5 or GPT 4, Thread, & Assistant | "2024-02-26T13:46:05.638000Z" | 7 | 78 | 0 | 0 | 2 | 1,321 | 894,603 | 2024-02-26T15:40:56.409Z | <p>Welcome <a class="mention" href="/u/rftaurust">@RFTaurust</a> - I’ll get started with a few answers here, I’m sure others will chime in soon to address the rest.</p>
<blockquote>
<p>In the docs it state that new Model is from 2023 - ???, as for ??? how long the range it included? is it until our current date? let say if now this question created on Feb 26th, 2024, is it mean the model knowledge has 0 gap date which up to date to this exact date or how long the gap between the knowledge is provided? I tried to search on documentation but there is no exact statement about this, maybe can be helpful if you put some kind of statement in there, let say there is a new movie which release next week, can it get what the schedule and which cinema that release it?</p>
</blockquote>
<p>For each group of models the training cut-off date is currently slightly different. This page provides you with a detailed breakdown: <a href="https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo" rel="noopener nofollow ugc">https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo</a><br>
GPT-4 turbo models have the most training data up to December 2023. This means, there remains a gap of a few months. Practically speaking, if you were to ask the model about an event that happened in January 2024, it would not know the answer to that unless you provide it with additional external information.</p>
<blockquote>
<p>Regarding streaming, Since we already know that Chat GPT itself using stream method to generate the answer, I’m curious regarding what is the biggest differences between using normal method & stream approach? is it make the right answer more precise than normal way, or is it make the cost more cheaper compared to the normal one with the benefit of fastest result? (Since I guess it’s somehow chunk the full context before returning it & in documentation only state iteratively and not touch any other reason for it so I’m curious about the advantage & disadvantage of both method)</p>
</blockquote>
<p>The primary purpose of streaming is to reduce the time until users see parts of the response. This is particularly useful when normally it would take a significant time for the model to provide a complete response. Streaming does not have an impact on the quality nor is it cheaper.</p>
<p>For the relationship between Assistants and threads, you should go over this official documentation, which should help to address some of your broader questions:</p>
<p><a href="https://platform.openai.com/docs/assistants/overview" class="onebox" target="_blank" rel="noopener nofollow ugc">https://platform.openai.com/docs/assistants/overview</a></p>
<p><a href="https://platform.openai.com/docs/api-reference/assistants" class="onebox" target="_blank" rel="noopener nofollow ugc">https://platform.openai.com/docs/api-reference/assistants</a></p> | 10 | 0 | 5b48a0acbf | 2 | [
575105,
497675,
534869,
523555,
573028
] | null | Welcome [@RFTaurust](/u/rftaurust) - I’ll get started with a few answers here, I’m sure others will chime in soon to address the rest.
>
> In the docs it state that new Model is from 2023 - ???, as for ??? how long the range it included? is it until our current date? let say if now this question created on Feb 26th, 2024, is it mean the model knowledge has 0 gap date which up to date to this exact date or how long the gap between the knowledge is provided? I tried to search on documentation but there is no exact statement about this, maybe can be helpful if you put some kind of statement in there, let say there is a new movie which release next week, can it get what the schedule and which cinema that release it?
>
>
>
For each group of models the training cut-off date is currently slightly different. This page provides you with a detailed breakdown: <https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo>
GPT-4 turbo models have the most training data up to December 2023. This means, there remains a gap of a few months. Practically speaking, if you were to ask the model about an event that happened in January 2024, it would not know the answer to that unless you provide it with additional external information.
>
> Regarding streaming, Since we already know that Chat GPT itself using stream method to generate the answer, I’m curious regarding what is the biggest differences between using normal method & stream approach? is it make the right answer more precise than normal way, or is it make the cost more cheaper compared to the normal one with the benefit of fastest result? (Since I guess it’s somehow chunk the full context before returning it & in documentation only state iteratively and not touch any other reason for it so I’m curious about the advantage & disadvantage of both method)
>
>
>
The primary purpose of streaming is to reduce the time until users see parts of the response. This is particularly useful when normally it would take a significant time for the model to provide a complete response. Streaming does not have an impact on the quality nor is it cheaper.
For the relationship between Assistants and threads, you should go over this official documentation, which should help to address some of your broader questions:
<https://platform.openai.com/docs/assistants/overview>
<https://platform.openai.com/docs/api-reference/assistants>
| api | neutral | 0.739566 | [
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] | gpt-4 | assistants-api | threads | api-threads | https://community.openai.com/t/655301 | https://community.openai.com/p/894603 | GPT Model Training | GPTs (4) |
655,408 | [
"api",
"chatgpt-team"
] | How do API keys and payments work in a Teams setting? | "2024-02-26T14:45:52.578000Z" | 7 | 61 | 1 | 0 | 2 | 260 | 894,502 | 2024-02-26T14:45:52.666Z | <p>I have a personal account that I’m considering moving to a Teams account. However, I want to understand how API keyd work after that change.</p>
<p>If I have API keys already assigned to me and I payed and I move to the Team workspace, are those API keys still mine and under my CC? What about if I want to create new ones? Will they be on the CC of the owner of the team plan or is each person in the plan allowed to create their own keys?</p>
<p>I’m trying to avoid two problems: one is the annoying need to constantly go back to the plan owner to put more money for my keys. And the other is that if I put money in my keys, I don’t want others to use them. Yes, I understand that once the key is copied, nobody else will see it so ,technically, I should be the only one eating credits on my keys.</p>
<p>Thanks,</p>
<p>L</p> | 7 | 0 | 3f74dcb156 | 1 | [
296824,
198888,
580501,
623888,
584822
] | 2 | I have a personal account that I’m considering moving to a Teams account. However, I want to understand how API keyd work after that change.
If I have API keys already assigned to me and I payed and I move to the Team workspace, are those API keys still mine and under my CC? What about if I want to create new ones? Will they be on the CC of the owner of the team plan or is each person in the plan allowed to create their own keys?
I’m trying to avoid two problems: one is the annoying need to constantly go back to the plan owner to put more money for my keys. And the other is that if I put money in my keys, I don’t want others to use them. Yes, I understand that once the key is copied, nobody else will see it so ,technically, I should be the only one eating credits on my keys.
Thanks,
L
| api | neutral | 0.867611 | [
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] | api | chatgpt-team | null | null | https://community.openai.com/t/655408 | https://community.openai.com/p/894502 | Key Management | API (2) |
655,408 | [
"api",
"chatgpt-team"
] | How do API keys and payments work in a Teams setting? | "2024-02-26T14:45:52.578000Z" | 7 | 61 | 1 | 0 | 2 | 260 | 894,573 | 2024-02-26T15:25:21.398Z | <p>A <strong>ChatGPT Plus or Team</strong> account is completely separate from the <strong>API</strong>.<br>
You don’t need any subscription to ChatGPT to use API, and team members there don’t mean anything to API access.</p>
<p>An API organization has its own “invite” system to let other accounts bill their usage to you and use your fine-tune models. They can create an API key and assign the organization to bill, or the API calls can specify the organization.</p>
<p>Inviting a bad actor can be expensive…</p> | 6 | 1 | b368833582 | 2 | [
296824,
198888,
580501,
623888,
584822
] | 2 | A **ChatGPT Plus or Team** account is completely separate from the **API**.
You don’t need any subscription to ChatGPT to use API, and team members there don’t mean anything to API access.
An API organization has its own “invite” system to let other accounts bill their usage to you and use your fine-tune models. They can create an API key and assign the organization to bill, or the API calls can specify the organization.
Inviting a bad actor can be expensive…
| api | neutral | 0.809286 | [
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] | api | chatgpt-team | null | null | https://community.openai.com/t/655408 | https://community.openai.com/p/894573 | Payment Platform | GPTs (4) |
655,408 | [
"api",
"chatgpt-team"
] | How do API keys and payments work in a Teams setting? | "2024-02-26T14:45:52.578000Z" | 7 | 61 | 1 | 0 | 2 | 260 | 894,580 | 2024-02-26T15:29:37.296Z | <p>Great, that’s what I was looking for. Thanks!</p>
<p>L</p> | 6 | 0 | 3f74dcb156 | 3 | [
296824,
198888,
580501,
623888,
584822
] | 2 | Great, that’s what I was looking for. Thanks!
L
| api | positive | 0.981363 | [
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] | api | chatgpt-team | null | null | https://community.openai.com/t/655408 | https://community.openai.com/p/894580 | Miscellaneous (20) | Emoji (8) |
655,453 | [] | Shortcut’s Ask ChatGPT have problem | "2024-02-26T15:12:38.415000Z" | 31 | 54 | 0 | 1 | 1 | 87 | 894,555 | 2024-02-26T15:12:38.491Z | <p>There is a problem with the IOS shortcut Ask ChatGPT. When I run it, I find that it will not chat continuously and will always create a new chat. When I chat with him in the shortcut, he will not remember the previous content, but I have closed the creation. The new chat function will still appear after the ChatGPT IOS application is updated, but there were no problems a month ago. You should refer to the relevant source code in the ChatGPT App a month ago.</p> | 13 | 0 | 1270165cab | 1 | [
31244,
497073,
316630,
589290,
457219
] | null | There is a problem with the IOS shortcut Ask ChatGPT. When I run it, I find that it will not chat continuously and will always create a new chat. When I chat with him in the shortcut, he will not remember the previous content, but I have closed the creation. The new chat function will still appear after the ChatGPT IOS application is updated, but there were no problems a month ago. You should refer to the relevant source code in the ChatGPT App a month ago.
| api/feedback | negative | 0.604955 | [
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] | null | null | null | null | https://community.openai.com/t/655453 | https://community.openai.com/p/894555 | Miscellaneous (2) | GPTs (4) |
654,970 | [
"api"
] | Natural language text - Emmanuel Katto | "2024-02-26T10:07:49.610000Z" | 7 | 48 | 0 | 0 | 2 | 60 | 893,982 | 2024-02-26T10:07:49.674Z | <p>Hi, I am Emmanuel Katto from UK. I wanna know how can developers effectively utilize OpenAI’s API to generate natural language text with specific characteristics or styles, such as formal, casual, humorous, or technical?</p> | 10 | 0 | 32090ab365 | 1 | [
552119,
633450,
15690,
648231,
360800
] | null | Hi, I am Emmanuel Katto from UK. I wanna know how can developers effectively utilize OpenAI’s API to generate natural language text with specific characteristics or styles, such as formal, casual, humorous, or technical?
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] | api | null | null | null | https://community.openai.com/t/654970 | https://community.openai.com/p/893982 | Deep Learning | Miscellaneous (27) |
654,970 | [
"api"
] | Natural language text - Emmanuel Katto | "2024-02-26T10:07:49.610000Z" | 7 | 48 | 0 | 0 | 2 | 60 | 894,560 | 2024-02-26T15:18:40.688Z | <p>The easiest way is to describe the style in the system prompt.</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://global.discourse-cdn.com/openai1/original/4X/c/d/9/cd926f26e7b83b655943316146cdaa41a5a41b2a.png" data-download-href="/uploads/short-url/tkzC8ZiZeNrhVBZDvsx3vxFdVZU.png?dl=1" title="Screenshot 2024-02-26 at 8.18.00 AM"><img src="https://global.discourse-cdn.com/openai1/optimized/4X/c/d/9/cd926f26e7b83b655943316146cdaa41a5a41b2a_2_690x269.png" alt="Screenshot 2024-02-26 at 8.18.00 AM" data-base62-sha1="tkzC8ZiZeNrhVBZDvsx3vxFdVZU" width="690" height="269" srcset="https://global.discourse-cdn.com/openai1/optimized/4X/c/d/9/cd926f26e7b83b655943316146cdaa41a5a41b2a_2_690x269.png, https://global.discourse-cdn.com/openai1/optimized/4X/c/d/9/cd926f26e7b83b655943316146cdaa41a5a41b2a_2_1035x403.png 1.5x, https://global.discourse-cdn.com/openai1/optimized/4X/c/d/9/cd926f26e7b83b655943316146cdaa41a5a41b2a_2_1380x538.png 2x" data-dominant-color="F5F5F6"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">Screenshot 2024-02-26 at 8.18.00 AM</span><span class="informations">2298×898 208 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p> | 6 | 0 | 40b33296b9 | 2 | [
552119,
633450,
15690,
648231,
360800
] | null | The easiest way is to describe the style in the system prompt.
[Screenshot 2024-02-26 at 8.18.00 AM2298×898 208 KB](https://global.discourse-cdn.com/openai1/original/4X/c/d/9/cd926f26e7b83b655943316146cdaa41a5a41b2a.png "Screenshot 2024-02-26 at 8.18.00 AM")
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] | api | null | null | null | https://community.openai.com/t/654970 | https://community.openai.com/p/894560 | Optimized Images | Miscellaneous (27) |
568,611 | [
"api",
"tts"
] | Request for Improved Persian Accent Support in Text-to-Speech Service | "2023-12-22T10:05:12.982000Z" | 31 | 292 | 0 | 0 | 2 | 342 | 768,042 | 2023-12-22T10:05:13.051Z | <p>Hello OpenAI Team,</p>
<p>I’m reaching out to share my observations and provide feedback on the text-to-speech (TTS) functionality, particularly regarding its performance in the Persian language. I’ve noticed that while the technology is adept at recognizing and converting Persian text to speech, the output seems to align more with an Afghan accent rather than a standard Persian (Iranian) accent.</p>
<p>I hypothesize that this issue might stem from the fact that the TTS system does not have an explicit input for specifying the desired language accent. Since Persian texts are linguistically similar across different regions (like Iran and Afghanistan), the system might not differentiate between the accents and defaults to an Afghan style, which differs significantly from the Tehrani accent or other regional Persian accents in Iran.</p>
<p>In an attempt to guide the TTS towards a Tehrani accent, I tried prefacing my texts with phrases like “this is a Persian text with a Tehrani accent,” but the results did not align with expectations. This leads me to suggest a possible enhancement: the introduction of a feature to explicitly specify the desired accent or dialect for a given language. Such a feature could enable users to choose between variations like Tehrani Persian, Afghan Persian, etc., thus providing more accurate and culturally relevant outputs.</p>
<p>The ability to fine-tune the accent in TTS is crucial for applications requiring linguistic and cultural precision, such as educational tools, localized content creation, and user interfaces designed for specific Persian-speaking communities.</p>
<p>I appreciate the complexity involved in developing nuanced TTS systems capable of capturing the subtleties of every language and dialect. However, enhancing the Persian TTS to include an option for selecting specific accents would be a significant step forward in making the technology more inclusive and widely applicable.</p>
<p>Thank you for your ongoing efforts to improve AI technology. I am looking forward to future developments that might address these nuances in TTS services.</p>
<p>Best regards,</p> | 16 | 0 | 2718c3e61a | 1 | [
500307,
571876,
477491,
532875,
400757
] | null | Hello OpenAI Team,
I’m reaching out to share my observations and provide feedback on the text-to-speech (TTS) functionality, particularly regarding its performance in the Persian language. I’ve noticed that while the technology is adept at recognizing and converting Persian text to speech, the output seems to align more with an Afghan accent rather than a standard Persian (Iranian) accent.
I hypothesize that this issue might stem from the fact that the TTS system does not have an explicit input for specifying the desired language accent. Since Persian texts are linguistically similar across different regions (like Iran and Afghanistan), the system might not differentiate between the accents and defaults to an Afghan style, which differs significantly from the Tehrani accent or other regional Persian accents in Iran.
In an attempt to guide the TTS towards a Tehrani accent, I tried prefacing my texts with phrases like “this is a Persian text with a Tehrani accent,” but the results did not align with expectations. This leads me to suggest a possible enhancement: the introduction of a feature to explicitly specify the desired accent or dialect for a given language. Such a feature could enable users to choose between variations like Tehrani Persian, Afghan Persian, etc., thus providing more accurate and culturally relevant outputs.
The ability to fine-tune the accent in TTS is crucial for applications requiring linguistic and cultural precision, such as educational tools, localized content creation, and user interfaces designed for specific Persian-speaking communities.
I appreciate the complexity involved in developing nuanced TTS systems capable of capturing the subtleties of every language and dialect. However, enhancing the Persian TTS to include an option for selecting specific accents would be a significant step forward in making the technology more inclusive and widely applicable.
Thank you for your ongoing efforts to improve AI technology. I am looking forward to future developments that might address these nuances in TTS services.
Best regards,
| api/feedback | neutral | 0.825589 | [
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] | api | tts | null | null | https://community.openai.com/t/568611 | https://community.openai.com/p/768042 | Languages | Artificial Intelligence |
568,611 | [
"api",
"tts"
] | Request for Improved Persian Accent Support in Text-to-Speech Service | "2023-12-22T10:05:12.982000Z" | 31 | 292 | 0 | 0 | 2 | 342 | 894,529 | 2024-02-26T14:58:33.799Z | <p>I hope you see a response in some way. Being able to fine tune accents would be amazing.</p> | 7 | 0 | ec5e7a9382 | 2 | [
500307,
571876,
477491,
532875,
400757
] | null | I hope you see a response in some way. Being able to fine tune accents would be amazing.
| api/feedback | positive | 0.875696 | [
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] | api | tts | null | null | https://community.openai.com/t/568611 | https://community.openai.com/p/894529 | Languages | Artificial Intelligence |
655,426 | [] | Text to Voice API - Calling different languages | "2024-02-26T14:56:26.001000Z" | 7 | 41 | 0 | 0 | 1 | 38 | 894,522 | 2024-02-26T14:56:26.063Z | <p>Hello!</p>
<p>Does anyone know how to invoke a different language for text to voice?</p>
<p>My current call for reference:</p>
<p>response = await async_openai_client.audio.speech.create(<br>
model=“tts-1-hd-1106”,<br>
voice=“nova”,<br>
input=text,<br>
response_format=‘opus’<br>
)</p>
<p>Thank you!</p> | 7 | 0 | ec5e7a9382 | 1 | [
400757,
477491,
475845,
617115,
485153
] | null | Hello!
Does anyone know how to invoke a different language for text to voice?
My current call for reference:
response = await async\_openai\_client.audio.speech.create(
model=“tts-1-hd-1106”,
voice=“nova”,
input=text,
response\_format=‘opus’
)
Thank you!
| api | neutral | 0.633391 | [
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] | null | null | null | null | https://community.openai.com/t/655426 | https://community.openai.com/p/894522 | Speech Recognition | Artificial Intelligence |
655,380 | [
"api",
"plugin-development",
"gpt-35-turbo"
] | Seeking Help with Excel VBA Script for OpenAI API Access to Custom Assistant - Timeout Issues | "2024-02-26T14:32:14.836000Z" | 7 | 49 | 0 | 0 | 1 | 279 | 894,472 | 2024-02-26T14:32:14.921Z | <p>Hello everyone,</p>
<p>I’m working on a project that involves integrating OpenAI’s API directly into Excel using a VBA script. My objective is to access a custom assistant I’ve configured with OpenAI, aiming to automate specific tasks within Excel by leveraging AI. I’ve made progress in setting up the API calls from the VBA script to interact with my custom assistant. However, I’ve hit a snag with timeouts, particularly when my script attempts to poll the status of the API call.</p>
<p>Here’s the relevant part of my VBA code that checks the API call status:<br>
’ 4. Poll the run status until it’s complete<br>
startTime = Timer<br>
Do While status = “queued” Or status = “in_progress”<br>
Call SetupHttpRequest(http, “GET”, “https :// api . openai . com / v1 / threads/” & threadId & “/runs/” & runId, OPENAI_API_KEY)<br>
http.send “”<br>
status = ExtractJsonValue(http . responseText, “status”)<br>
If Timer - startTime > 29 Then<br>
askOpenAIAssistant = “Timeout waiting for the run to complete.”<br>
Exit Function<br>
End If<br>
DoEvents<br>
Loop</p>
<p>Despite my efforts to monitor the run status until completion or a 29-second timeout threshold, I frequently face timeouts. This issue has been a significant roadblock in successfully leveraging my custom assistant through Excel.</p>
<p>I’m reaching out for advice or insights from anyone who has successfully set up a similar Excel VBA integration with OpenAI’s API, especially when accessing a custom assistant. How have you managed or avoided these timeout issues? Any tips, strategies, or code examples that could help me refine my VBA script to handle API responses more effectively and avoid these frustrating timeouts would be immensely helpful.</p>
<p>Thank you all for your time and assistance. I’m looking forward to any guidance you can provide!</p> | 7 | 0 | f3eb086197 | 1 | [
344895,
192276,
557536,
411252,
500985
] | null | Hello everyone,
I’m working on a project that involves integrating OpenAI’s API directly into Excel using a VBA script. My objective is to access a custom assistant I’ve configured with OpenAI, aiming to automate specific tasks within Excel by leveraging AI. I’ve made progress in setting up the API calls from the VBA script to interact with my custom assistant. However, I’ve hit a snag with timeouts, particularly when my script attempts to poll the status of the API call.
Here’s the relevant part of my VBA code that checks the API call status:
’ 4. Poll the run status until it’s complete
startTime = Timer
Do While status = “queued” Or status = “in\_progress”
Call SetupHttpRequest(http, “GET”, “https :// api . openai . com / v1 / threads/” & threadId & “/runs/” & runId, OPENAI\_API\_KEY)
http.send “”
status = ExtractJsonValue(http . responseText, “status”)
If Timer - startTime > 29 Then
askOpenAIAssistant = “Timeout waiting for the run to complete.”
Exit Function
End If
DoEvents
Loop
Despite my efforts to monitor the run status until completion or a 29-second timeout threshold, I frequently face timeouts. This issue has been a significant roadblock in successfully leveraging my custom assistant through Excel.
I’m reaching out for advice or insights from anyone who has successfully set up a similar Excel VBA integration with OpenAI’s API, especially when accessing a custom assistant. How have you managed or avoided these timeout issues? Any tips, strategies, or code examples that could help me refine my VBA script to handle API responses more effectively and avoid these frustrating timeouts would be immensely helpful.
Thank you all for your time and assistance. I’m looking forward to any guidance you can provide!
| api | neutral | 0.599423 | [
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] | api | plugin-development | gpt-35-turbo | null | https://community.openai.com/t/655380 | https://community.openai.com/p/894472 | Performance (2) | Tokenization (2) |
543,854 | [
"gpt-4"
] | Gpt-4-1106-preview get slow | "2023-12-05T07:27:52.904000Z" | 7 | 2,295 | 0 | 2 | 5 | 496 | 730,523 | 2023-12-05T07:27:52.989Z | <p>I’ve been using a very simple langchain code to create a chatbot powered by gpt-4-turbo.</p>
<p>Until December 4th, the speed was consistently fast, but in the past two days, it has suddenly become very slow. (Approximately from 30 tokens/S dropped to 10 tokens/S)</p>
<p>I haven’t made any changes to the code.</p>
<p>Additionally, I have recorded the model’s fingerprint, and it seems that OpenAI began updating the model around December 1st:</p>
<ul>
<li>2023-12-01 14:35:15,002 - openai_fp_log - model: gpt-4-1106-preview, fingerprint: fp_a24b4d720c</li>
<li>2023-12-01 14:39:27,898 - openai_fp_log - model: gpt-4-1106-preview, fingerprint: fp_a24b4d720c</li>
<li>2023-12-01 14:42:57,834 - openai_fp_log - model: gpt-4-1106-preview, fingerprint: fp_a24b4d720c</li>
<li>2023-12-04 20:00:22,212 - openai_fp_log - model: gpt-4-1106-preview, fingerprint: fp_<strong>2eb0b038f6</strong></li>
<li>2023-12-04 20:56:04,723 - openai_fp_log - model: gpt-4-1106-preview, fingerprint: fp_a24b4d720c</li>
<li>2023-12-04 20:59:42,837 - openai_fp_log - model: gpt-4-1106-preview, fingerprint: fp_a24b4d720c</li>
<li>2023-12-05 09:48:43,225 - openai_fp_log - model: gpt-4-1106-preview, fingerprint: fp_<strong>d2455ee9e0</strong></li>
<li>2023-12-05 10:10:41,939 - openai_fp_log - model: gpt-4-1106-preview, fingerprint: fp_a24b4d720c</li>
<li>2023-12-05 11:12:09,103 - openai_fp_log - model: gpt-4-1106-preview, fingerprint: fp_a24b4d720c</li>
<li>2023-12-05 11:34:53,838 - openai_fp_log - model: gpt-4-1106-preview, fingerprint: fp_a24b4d720c</li>
<li>2023-12-05 11:43:53,015 - openai_fp_log - model: gpt-4-1106-preview, fingerprint: fp_a24b4d720c</li>
<li>2023-12-05 12:17:15,388 - openai_fp_log - model: gpt-4-1106-preview, fingerprint: fp_a24b4d720c</li>
</ul>
<p>The code I’m using is as follows:</p>
<pre><code class="lang-auto">llm = OpenAI(model_name=_self.openai_model, temperature=0, streaming=True)
chain = ConversationChain(llm=llm, memory=memory, verbose=True)
chain.run("xxxxxx")
</code></pre>
<p>Additionally, I’ve noticed that now when inputting the same question, gpt4-turbo’s responses in English are over twice as fast as those in Chinese, despite the response length and semantic content being similar."</p>
<p>Has the speed of the gpt4-turbo model really decreased?Or maybe my code is not adapted to the new version of the model?Will the speed increase in the release version in the future?</p> | 122 | 0 | 4556783062 | 1 | [
555383,
607966,
640146,
468546,
203468
] | null | I’ve been using a very simple langchain code to create a chatbot powered by gpt-4-turbo.
Until December 4th, the speed was consistently fast, but in the past two days, it has suddenly become very slow. (Approximately from 30 tokens/S dropped to 10 tokens/S)
I haven’t made any changes to the code.
Additionally, I have recorded the model’s fingerprint, and it seems that OpenAI began updating the model around December 1st:
* 2023-12-01 14:35:15,002 - openai\_fp\_log - model: gpt-4-1106-preview, fingerprint: fp\_a24b4d720c
* 2023-12-01 14:39:27,898 - openai\_fp\_log - model: gpt-4-1106-preview, fingerprint: fp\_a24b4d720c
* 2023-12-01 14:42:57,834 - openai\_fp\_log - model: gpt-4-1106-preview, fingerprint: fp\_a24b4d720c
* 2023-12-04 20:00:22,212 - openai\_fp\_log - model: gpt-4-1106-preview, fingerprint: fp\_**2eb0b038f6**
* 2023-12-04 20:56:04,723 - openai\_fp\_log - model: gpt-4-1106-preview, fingerprint: fp\_a24b4d720c
* 2023-12-04 20:59:42,837 - openai\_fp\_log - model: gpt-4-1106-preview, fingerprint: fp\_a24b4d720c
* 2023-12-05 09:48:43,225 - openai\_fp\_log - model: gpt-4-1106-preview, fingerprint: fp\_**d2455ee9e0**
* 2023-12-05 10:10:41,939 - openai\_fp\_log - model: gpt-4-1106-preview, fingerprint: fp\_a24b4d720c
* 2023-12-05 11:12:09,103 - openai\_fp\_log - model: gpt-4-1106-preview, fingerprint: fp\_a24b4d720c
* 2023-12-05 11:34:53,838 - openai\_fp\_log - model: gpt-4-1106-preview, fingerprint: fp\_a24b4d720c
* 2023-12-05 11:43:53,015 - openai\_fp\_log - model: gpt-4-1106-preview, fingerprint: fp\_a24b4d720c
* 2023-12-05 12:17:15,388 - openai\_fp\_log - model: gpt-4-1106-preview, fingerprint: fp\_a24b4d720c
The code I’m using is as follows:
```
llm = OpenAI(model_name=_self.openai_model, temperature=0, streaming=True)
chain = ConversationChain(llm=llm, memory=memory, verbose=True)
chain.run("xxxxxx")
```
Additionally, I’ve noticed that now when inputting the same question, gpt4-turbo’s responses in English are over twice as fast as those in Chinese, despite the response length and semantic content being similar."
Has the speed of the gpt4-turbo model really decreased?Or maybe my code is not adapted to the new version of the model?Will the speed increase in the release version in the future?
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] | gpt-4 | null | null | null | https://community.openai.com/t/543854 | https://community.openai.com/p/730523 | Campaign | GPTs (4) |
543,854 | [
"gpt-4"
] | Gpt-4-1106-preview get slow | "2023-12-05T07:27:52.904000Z" | 7 | 2,295 | 0 | 2 | 5 | 496 | 732,704 | 2023-12-06T03:42:00.750Z | <p>I’ve also encountered the same issue as you. The gpt-4-1106-preview model has been very slow over the past 1-2 days.</p> | 88 | 0 | 963e9ab157 | 2 | [
555383,
607966,
640146,
468546,
203468
] | null | I’ve also encountered the same issue as you. The gpt-4-1106-preview model has been very slow over the past 1-2 days.
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] | gpt-4 | null | null | null | https://community.openai.com/t/543854 | https://community.openai.com/p/732704 | Models | GPTs (4) |
543,854 | [
"gpt-4"
] | Gpt-4-1106-preview get slow | "2023-12-05T07:27:52.904000Z" | 7 | 2,295 | 0 | 2 | 5 | 496 | 750,565 | 2023-12-14T05:45:48.828Z | <p>Yes, response of this model is very slow. When we switch to GPT-4 model, the response if fast, but we cannot retrieve from files uploaded, so its not much useful.</p> | 65 | 0 | af9f88b55e | 3 | [
555383,
607966,
640146,
468546,
203468
] | null | Yes, response of this model is very slow. When we switch to GPT-4 model, the response if fast, but we cannot retrieve from files uploaded, so its not much useful.
| api | negative | 0.847481 | [
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] | gpt-4 | null | null | null | https://community.openai.com/t/543854 | https://community.openai.com/p/750565 | GPT Model Training | GPTs (4) |
543,854 | [
"gpt-4"
] | Gpt-4-1106-preview get slow | "2023-12-05T07:27:52.904000Z" | 7 | 2,295 | 0 | 2 | 5 | 496 | 751,729 | 2023-12-14T17:23:58.654Z | <p>I’ve also noticed a slow down. Originally turbo was 3 times faster, but now they are approximately the same speed.</p> | 53 | 0 | 535d26c916 | 4 | [
555383,
607966,
640146,
468546,
203468
] | null | I’ve also noticed a slow down. Originally turbo was 3 times faster, but now they are approximately the same speed.
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] | gpt-4 | null | null | null | https://community.openai.com/t/543854 | https://community.openai.com/p/751729 | GPUs, Performance, Compute | Payment (4) |
543,854 | [
"gpt-4"
] | Gpt-4-1106-preview get slow | "2023-12-05T07:27:52.904000Z" | 7 | 2,295 | 0 | 2 | 5 | 496 | 771,735 | 2023-12-25T04:07:07.348Z | <p>As of today (December 25, 2023), the performance has largely recovered to its previous state, indicating that OpenAI is actively refining the model behind the scenes.</p> | 39 | 0 | 4556783062 | 5 | [
555383,
607966,
640146,
468546,
203468
] | null | As of today (December 25, 2023), the performance has largely recovered to its previous state, indicating that OpenAI is actively refining the model behind the scenes.
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] | gpt-4 | null | null | null | https://community.openai.com/t/543854 | https://community.openai.com/p/771735 | Miscellaneous (22) | API (2) |
543,854 | [
"gpt-4"
] | Gpt-4-1106-preview get slow | "2023-12-05T07:27:52.904000Z" | 7 | 2,295 | 0 | 2 | 5 | 496 | 894,412 | 2024-02-26T14:01:18.281Z | <p>Hello everyone, how’s the speed now? Has it improved or is it still slow? I’m considering switching to GPT-4-1106-preview, but I’m unsure if the speed issue persists in that version.</p> | 4 | 0 | e76f5f4608 | 6 | [
555383,
607966,
640146,
468546,
203468
] | null | Hello everyone, how’s the speed now? Has it improved or is it still slow? I’m considering switching to GPT-4-1106-preview, but I’m unsure if the speed issue persists in that version.
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] | gpt-4 | null | null | null | https://community.openai.com/t/543854 | https://community.openai.com/p/894412 | Models | GPTs (4) |
655,182 | [
"api",
"api-billing"
] | Pay with invoice instead of card | "2024-02-26T12:25:55.132000Z" | 7 | 56 | 0 | 0 | 1 | 273 | 894,234 | 2024-02-26T12:25:55.202Z | <p>Hello everyone,</p>
<p>I hope you’re all doing well! I’ve been digging through the forum for a while, trying to find an answer to a question that I believe might be common, but I haven’t had much luck so far. It’s about card payments being the only payment option.</p>
<p>Background:<br>
I’m here representing a medium-sized SaaS company, and we’re eager to adopt the API more. I’ve been evaluating the licensing options, and it seems like the Enterprise license is aimed at larger organizations than ours, which makes it not the ideal fit for us at the moment. Therefore I imagine the API.</p>
<p>One of our main challenges is related to payment processing. Our company, like many in our region, primarily deals with supplier payments through invoices rather than credit card transactions. I understand the need of a secure payment system, especially to prevent misuse and not use tokens without paying. However, the reliance on credit card payments is somewhat out of step with our standard financial operations.</p>
<p>This leads me to wonder if we’re overlooking alternative payment options that might be more aligned with our business practices. Is credit card payment truly the only method available for medium-sized companies like ours looking to use the API more intensively? I’m keen to learn if there are other arrangements we haven’t discovered yet, as I’m sure we’re not the only ones in this boat.</p>
<p>Thank you in advance for any insights!</p>
<p>I’m really impressed with the service so far and are looking forward to integrating it more deeply into our work.</p> | 8 | 0 | 175552862e | 1 | [
474834,
163845,
330506,
20894,
630596
] | null | Hello everyone,
I hope you’re all doing well! I’ve been digging through the forum for a while, trying to find an answer to a question that I believe might be common, but I haven’t had much luck so far. It’s about card payments being the only payment option.
Background:
I’m here representing a medium-sized SaaS company, and we’re eager to adopt the API more. I’ve been evaluating the licensing options, and it seems like the Enterprise license is aimed at larger organizations than ours, which makes it not the ideal fit for us at the moment. Therefore I imagine the API.
One of our main challenges is related to payment processing. Our company, like many in our region, primarily deals with supplier payments through invoices rather than credit card transactions. I understand the need of a secure payment system, especially to prevent misuse and not use tokens without paying. However, the reliance on credit card payments is somewhat out of step with our standard financial operations.
This leads me to wonder if we’re overlooking alternative payment options that might be more aligned with our business practices. Is credit card payment truly the only method available for medium-sized companies like ours looking to use the API more intensively? I’m keen to learn if there are other arrangements we haven’t discovered yet, as I’m sure we’re not the only ones in this boat.
Thank you in advance for any insights!
I’m really impressed with the service so far and are looking forward to integrating it more deeply into our work.
| api | neutral | 0.611618 | [
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] | api | api-billing | null | null | https://community.openai.com/t/655182 | https://community.openai.com/p/894234 | Payment Services | Tokenization (2) |