Spaces:
Runtime error
Runtime error
Fixes chat
Browse files- gradio_app.py +6 -5
gradio_app.py
CHANGED
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@@ -170,10 +170,10 @@ class TextGeneration:
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input_text,
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**generation_kwargs,
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)[0]["generated_text"]
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if generation_kwargs["do_clean"]:
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generated_text = cleaner.clean_txt(generated_text)
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if generated_text.strip().startswith(input_text):
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generated_text = generated_text.replace(input_text, "", 1).strip()
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if generated_text:
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if previous_text and previous_text != text:
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diff = [
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@@ -258,9 +258,10 @@ def chat_with_gpt(agent, user, context, user_message, history, max_length, top_k
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break
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context += history_context
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for _ in range(5):
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-
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if DEBUG:
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print("\n
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# response = response.split("\n")[-1]
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# if agent in response and response.split(agent)[-1]:
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# response = response.split(agent)[-1]
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@@ -268,7 +269,7 @@ def chat_with_gpt(agent, user, context, user_message, history, max_length, top_k
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# response = response.split(user)[-1]
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# Take the first response
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response = [
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r for r in response.split(f"{AGENT}:") if r.strip()
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][0].split(USER)[0].replace(f"{AGENT}:", "\n").strip()
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if response[0] in string.punctuation:
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response = response[1:].strip()
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input_text,
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**generation_kwargs,
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)[0]["generated_text"]
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if generated_text.strip().startswith(input_text):
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generated_text = generated_text.replace(input_text, "", 1).strip()
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if generation_kwargs["do_clean"]:
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generated_text = cleaner.clean_txt(generated_text)
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if generated_text:
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if previous_text and previous_text != text:
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diff = [
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break
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context += history_context
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for _ in range(5):
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prompt = f"{context}\n\n{user}: {message}.\n"
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response = generator.generate(prompt, generation_kwargs)[0]
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if DEBUG:
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print("\n-----\n" + response + "\n-----\n")
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# response = response.split("\n")[-1]
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# if agent in response and response.split(agent)[-1]:
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# response = response.split(agent)[-1]
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# response = response.split(user)[-1]
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# Take the first response
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response = [
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r for r in response.replace(prompt, "").split(f"{AGENT}:") if r.strip()
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][0].split(USER)[0].replace(f"{AGENT}:", "\n").strip()
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if response[0] in string.punctuation:
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response = response[1:].strip()
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