HI ALL , BELOW IS MY CODE:
from langchain.llms import HuggingFaceHub
from langchain import PromptTemplate, LLMChain
repo_id=“mistralai/Mistral-7B-Instruct-v0.2”
response=llm.invoke(“what is the capital of USA”)
print(response)
ERROR BELOW:
1 Like
Ongoing issue.
opened 04:58PM - 06 May 25 UTC
bug
### Describe the bug
The InferenceClient API still does not support many of the… tasks that can be hosted at inference endpoints, but gives a deprecation warning when using `.post` to get around this.
### Reproduction
```python
from huggingface_hub import InferenceClient, get_inference_endpoint
import json
# Get endpoint and create client
MODEL_NAME = "YOUR_MODEL_NAME_OR_ENDPOINT_NAME"
NAMESPACE = "YOUR_NAMESPACE"
endpoint = get_inference_endpoint(MODEL_NAME, namespace=NAMESPACE)
client = InferenceClient(endpoint.url, timeout=10)
# Test data
query = "What is the capital of France?"
document = "Paris is the capital of France."
sentence_ranking_style_inputs = [[query, document]]
text_classification_style_inputs = [{"text": query, "text_pair": document}]
# 1. Using post method
response_bytes = client.post(json={"inputs": sentence_ranking_style_inputs})
print(json.loads(response_bytes))
# Problem: post method has deprecation warning
# 2. Using text_classification task
try:
result = client.text_classification(text_classification_style_inputs) # There's no way to inject the inputs format that would have worked on this task for reranking
print(result)
except Exception as e:
print(f"text_classification error: {e}")
# Problem: text_classification doesn't properly support text pairs format needed for reranking/cross-encoding
# 3. Using sentence_similarity task
try:
result = client.sentence_similarity(sentence_ranking_style_inputs) # There's no direct way to inject the inputs format that would have worked on this task for reranking
print(result)
except Exception as e:
print(f"sentence_similarity error: {e}")
# Problem: No direct support for sentence ranking despite endpoint supporting this task
```
Ideally, the sentence_ranking task is supported.
### Logs
```shell
```
### System info
```shell
- huggingface_hub version: 0.30.2
- Platform: macOS-15.4-arm64-arm-64bit
- Python version: 3.12.10
- Running in iPython ?: No
- Running in notebook ?: No
- Running in Google Colab ?: No
- Running in Google Colab Enterprise ?: No
- Token path ?: redacted
- Has saved token ?: False
- Configured git credential helpers: redacted
- FastAI: N/A
- Tensorflow: N/A
- Torch: 2.7.0
- Jinja2: 3.1.6
- Graphviz: N/A
- keras: N/A
- Pydot: N/A
- Pillow: 11.2.1
- hf_transfer: N/A
- gradio: N/A
- tensorboard: N/A
- numpy: 1.26.4
- pydantic: 2.11.4
- aiohttp: 3.11.18
- hf_xet: N/A
- ENDPOINT: https://huggingface.co
- HF_HUB_CACHE: redacted
- HF_ASSETS_CACHE: redacted
- HF_TOKEN_PATH: redacted
- HF_STORED_TOKENS_PATH: redacted
- HF_HUB_OFFLINE: False
- HF_HUB_DISABLE_TELEMETRY: False
- HF_HUB_DISABLE_PROGRESS_BARS: None
- HF_HUB_DISABLE_SYMLINKS_WARNING: False
- HF_HUB_DISABLE_EXPERIMENTAL_WARNING: False
- HF_HUB_DISABLE_IMPLICIT_TOKEN: False
- HF_HUB_ENABLE_HF_TRANSFER: False
- HF_HUB_ETAG_TIMEOUT: 10
- HF_HUB_DOWNLOAD_TIMEOUT: 10
```
Solution for SentenceTransformers:
ANY SOLUTION GUYS ??
KINDLY PLEASE PROVIDE THE SOLUTION
1 Like
Hmm… It seems that this cannot be resolved with a user patch…
STILL NO SOLUTION OVER THIS ???
KINDLY RESOLVE: AttributeError: ‘InferenceClient’ object has no attribute ‘post’
1 Like
Seems WIP?
main ← copilot/fix-3055
opened 05:55PM - 23 May 25 UTC
Thanks for assigning this issue to me. I'm starting to work on it and will keep … this PR's description up to date as I form a plan and make progress.
Original issue description:
> ### Describe the bug
>
> The InferenceClient API still does not support many of the tasks that can be hosted at inference endpoints, but gives a deprecation warning when using `.post` to get around this.
>
> ### Reproduction
>
> ```python
> from huggingface_hub import InferenceClient, get_inference_endpoint
> import json
>
> # Get endpoint and create client
> MODEL_NAME = "YOUR_MODEL_NAME_OR_ENDPOINT_NAME"
> NAMESPACE = "YOUR_NAMESPACE"
> endpoint = get_inference_endpoint(MODEL_NAME, namespace=NAMESPACE)
> client = InferenceClient(endpoint.url, timeout=10)
>
> # Test data
> query = "What is the capital of France?"
> document = "Paris is the capital of France."
> sentence_ranking_style_inputs = [[query, document]]
> text_classification_style_inputs = [{"text": query, "text_pair": document}]
>
> # 1. Using post method
> response_bytes = client.post(json={"inputs": sentence_ranking_style_inputs})
> print(json.loads(response_bytes))
> # Problem: post method has deprecation warning
>
> # 2. Using text_classification task
> try:
> result = client.text_classification(text_classification_style_inputs) # There's no way to inject the inputs format that would have worked on this task for reranking
> print(result)
> except Exception as e:
> print(f"text_classification error: {e}")
> # Problem: text_classification doesn't properly support text pairs format needed for reranking/cross-encoding
>
> # 3. Using sentence_similarity task
> try:
> result = client.sentence_similarity(sentence_ranking_style_inputs) # There's no direct way to inject the inputs format that would have worked on this task for reranking
> print(result)
> except Exception as e:
> print(f"sentence_similarity error: {e}")
> # Problem: No direct support for sentence ranking despite endpoint supporting this task
> ```
>
> Ideally, the sentence_ranking task is supported.
>
> ### Logs
>
> ```shell
>
> ```
>
> ### System info
>
> ```shell
> - huggingface_hub version: 0.30.2
> - Platform: macOS-15.4-arm64-arm-64bit
> - Python version: 3.12.10
> - Running in iPython ?: No
> - Running in notebook ?: No
> - Running in Google Colab ?: No
> - Running in Google Colab Enterprise ?: No
> - Token path ?: redacted
> - Has saved token ?: False
> - Configured git credential helpers: redacted
> - FastAI: N/A
> - Tensorflow: N/A
> - Torch: 2.7.0
> - Jinja2: 3.1.6
> - Graphviz: N/A
> - keras: N/A
> - Pydot: N/A
> - Pillow: 11.2.1
> - hf_transfer: N/A
> - gradio: N/A
> - tensorboard: N/A
> - numpy: 1.26.4
> - pydantic: 2.11.4
> - aiohttp: 3.11.18
> - hf_xet: N/A
> - ENDPOINT: https://huggingface.co
> - HF_HUB_CACHE: redacted
> - HF_ASSETS_CACHE: redacted
> - HF_TOKEN_PATH: redacted
> - HF_STORED_TOKENS_PATH: redacted
> - HF_HUB_OFFLINE: False
> - HF_HUB_DISABLE_TELEMETRY: False
> - HF_HUB_DISABLE_PROGRESS_BARS: None
> - HF_HUB_DISABLE_SYMLINKS_WARNING: False
> - HF_HUB_DISABLE_EXPERIMENTAL_WARNING: False
> - HF_HUB_DISABLE_IMPLICIT_TOKEN: False
> - HF_HUB_ENABLE_HF_TRANSFER: False
> - HF_HUB_ETAG_TIMEOUT: 10
> - HF_HUB_DOWNLOAD_TIMEOUT: 10
> ```
Fixes #3055.
---
💡 You can make Copilot smarter by setting up custom instructions, customizing its development environment and configuring Model Context Protocol (MCP) servers. Learn more [Copilot coding agent tips](https://gh.io/copilot-coding-agent-tips) in the docs.
It may be possible to fix this on the langchain side, but I don’t think it has been done yet.
🦜🔗 Build context-aware reasoning applications
You’re using InferenceClient which doesn’t have a .post() method. LangChain expects HuggingFaceHub for this to work.
Swap it to:
from langchain.llms import HuggingFaceHub
That’ll stop the .post() error.
Solution provided by Triskel Data Deterministic AI
1 Like
your solution is NOT WORKING
1 Like
Dear Respected Brother, I never degenerated your solution… When I ran your code on colab, its showing Bugs or error…
Good day bro
1 Like
