Changes for collinear sdk

app.py

@@ -1,65 +1,27 @@
 import gradio as gr
 from collinear import Collinear
-conv_template = Template(
- """
- # Context:
- {{ document }}
- 
- # Claim:
- {% for message in conversation %}
- {{ message.role }}: {{ message.content }}
- {% endfor %}
- """
-)
+import os
+collinear = Collinear(access_token=os.getenv('COLLINEAR_API_KEY'))
 
-qa_template = Template(
- """
- # Context:
- {{ document }}
- 
- # Claim:
- user: {{ question }}
- assistant: {{ answer }}
- """
-)
-
-nli_template = Template(
- """
- # Context:
- {{ document }}
- 
- # Claim:
- assistant: {{ claim }}
- """
-)
-
-
-# Function to dynamically update inputs based on the input style
 def update_inputs(input_style):
- # if input_style == "Conv":
- # return gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
- # elif input_style == "NLI":
- # return gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
- # elif input_style == "QA format":
- # return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True)
+ if input_style == "Conv":
+ return gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
+ elif input_style == "NLI":
+ return gr.update(visible=True), gr.update(visible=False), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
+ elif input_style == "QA format":
+ return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), gr.update(visible=True)
 
 
 # Function to judge reliability based on the selected input format
-def judge_reliability(input_style, document, conversation, claim, question, answer):
- # with torch.no_grad():
- # if input_style == "Conv":
- # conversation = json.loads(conversation)
- # text = conv_template.render(document=document, conversation=conversation)
- # elif input_style == "NLI":
- # text = nli_template.render(document=document, claim=claim)
- # elif input_style == "QA format":
- # text = qa_template.render(document=document, question=question, answer=answer)
-
- # print(text)
- 
- # outputs = model_pipeline(text)
- # results = f"Reliability Judge Outputs: {outputs}"
- # return results
+async def judge_reliability(input_style, document, conversation, claim, question, answer):
+ if input_style == "Conv":
+ outputs= await collinear.judge.veritas.conversation(document,conversation[:-1],conversation[-1])
+ elif input_style == "NLI":
+ outputs = await collinear.judge.veritas.natural_language_inference(document,claim)
+ elif input_style == "QA format":
+ outputs = await collinear.judge.veritas.question_answer(document,question,answer)
+ results = f"Reliability Judge Outputs: {outputs}"
+ return results