Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

added open source app streaming #217

Merged
merged 2 commits into from
Jul 10, 2023
Merged

added open source app streaming #217

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
f0eead2
added open source app streaming
Jul 10, 2023
9de7432
added readme update
Jul 10, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -224,7 +224,7 @@ print(naval_chat_bot.chat("what did the author say about happiness?"))

### Stream Response

- You can add config to your query method to stream responses like ChatGPT does. You would require a downstream handler to render the chunk in your desirable format. Currently only supports OpenAI model.
- You can add config to your query method to stream responses like ChatGPT does. You would require a downstream handler to render the chunk in your desirable format. Supports both OpenAI model and OpenSourceApp.

- To use this, instantiate a `QueryConfig` or `ChatConfig` object with `stream=True`. Then pass it to the `.chat()` or `.query()` method. The following example iterates through the chunks and prints them as they appear.

Expand Down
3 changes: 2 additions & 1 deletion embedchain/embedchain.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -350,14 +350,15 @@ def __init__(self, config: InitConfig = None):
print("Successfully loaded open source embedding model.")
super().__init__(config)

def get_llm_model_answer(self, prompt):
def get_llm_model_answer(self, prompt, config: ChatConfig):
from gpt4all import GPT4All

global gpt4all_model
if gpt4all_model is None:
gpt4all_model = GPT4All("orca-mini-3b.ggmlv3.q4_0.bin")
response = gpt4all_model.generate(
prompt=prompt,
streaming=config.stream
)
return response

Expand Down