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Revert "Revert "Add support for multiple LLM Providers (#60)"" (#83)

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* Revert "Revert "Add support for multiple LLM Providers (#60)""

This reverts commit 43d6bc80e9.

* wip

Signed-off-by: José Ulises Niño Rivera <junr03@users.noreply.github.com>

* Revert "wip"

This reverts commit 7c4dde5d1f.

* fix parameter name

Signed-off-by: José Ulises Niño Rivera <junr03@users.noreply.github.com>

* force use openai

---------

Signed-off-by: José Ulises Niño Rivera <junr03@users.noreply.github.com>
Co-authored-by: Adil Hafeez <adil@katanemo.com>
This commit is contained in:
José Ulises Niño Rivera 2024-09-26 00:15:17 -06:00 • committed by GitHub
parent 370f3bb2c5
commit 9ea6bb0d73
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12 changed files with 457 additions and 127 deletions
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23
chatbot_ui/app/run.py
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@ -6,27 +6,32 @@ from dotenv import load_dotenv
load_dotenv()
OPEN_API_KEY=os.getenv("OPENAI_API_KEY")
OPENAI_API_KEY=os.getenv("OPENAI_API_KEY")
MISTRAL_API_KEY = os.getenv("MISTRAL_API_KEY")
CHAT_COMPLETION_ENDPOINT = os.getenv("CHAT_COMPLETION_ENDPOINT")
MODEL_NAME = os.getenv("MODEL_NAME", "gpt-3.5-turbo")
log.info("CHAT_COMPLETION_ENDPOINT: ", CHAT_COMPLETION_ENDPOINT)
client = OpenAI(api_key=OPEN_API_KEY, base_url=CHAT_COMPLETION_ENDPOINT)
client = OpenAI(api_key=OPENAI_API_KEY, base_url=CHAT_COMPLETION_ENDPOINT)
def predict(message, history):
# history_openai_format = []
# for human, assistant in history:
# history_openai_format.append({"role": "user", "content": human })
# history_openai_format.append({"role": "assistant", "content":assistant})
history.append({"role": "user", "content": message})
log.info("CHAT_COMPLETION_ENDPOINT: ", CHAT_COMPLETION_ENDPOINT)
log.info("history: ", history)
# Custom headers
custom_headers = {
'x-bolt-openai-api-key': f"{OPENAI_API_KEY}",
'x-bolt-mistral-api-key': f"{MISTRAL_API_KEY}",
'x-bolt-deterministic-provider': 'openai',
}
try:
response = client.chat.completions.create(model=MODEL_NAME,
messages= history,
temperature=1.0
temperature=1.0,
extra_headers=custom_headers
)
except Exception as e:
log.info(e)
@ -36,10 +41,6 @@ def predict(message, history):
log.info("Error calling gateway API: {}".format(e.message))
raise gr.Error("Error calling gateway API: {}".format(e.message))
# for chunk in response:
# if chunk.choices[0].delta.content is not None:
# partial_message = partial_message + chunk.choices[0].delta.content
# yield partial_message
choices = response.choices
message = choices[0].message
content = message.content