Update funcs.py
Browse files
funcs.py
CHANGED
@@ -70,13 +70,7 @@ def generate_triggers_img(items):
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triggers_img = Image.open('triggeres.png')
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return triggers_img
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class process_session():
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def __init__(self):
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self.session_conversation=[]
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def get_doc_response_emotions(self, user_message, therapy_session_conversation):
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user_messages = []
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user_messages.append(user_message)
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emotion_set = detect_emotions(user_message)
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@@ -95,7 +89,7 @@ class process_session():
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therapy_session_conversation.append(["User: "+user_message, "Therapist: "+doc_response])
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print(f"User's message: {user_message}")
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print(f"RAG Matching message: {dials_embeddings.iloc[top_match_index]['Patient']}")
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@@ -103,7 +97,9 @@ class process_session():
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return '', therapy_session_conversation, emotions_msg
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def summarize_and_recommend(
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session_time = str(datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
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session_conversation_processed = self.session_conversation.copy()
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@@ -116,7 +112,7 @@ class process_session():
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model="tiiuae/falcon-180b-chat",
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messages=[
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{"role": "system", "content": """You are an Expert Cognitive Behavioural Therapist and Precis writer.
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Summarize the below user content <<<session_conversation_processed>>> into useful, ethical, relevant and realistic phrases with a format
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Session Time:
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Summary of the patient messages: #in two to four sentences
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Summary of therapist messages: #in two to three sentences:
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@@ -137,7 +133,7 @@ class process_session():
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model="tiiuae/falcon-180b-chat",
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messages=[
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{"role": "system", "content": """You are an expert Cognitive Behavioural Therapist.
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Based on the full summary <<<full_summary>>> provide clinically valid, useful, appropriate action plan for the Patient as a bullted list.
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The list shall contain both medical and non medical prescriptions, dos and donts. The format of response shall be in passive voice with proper tense.
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- The patient is referred to........ #in one sentence
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- The patient is advised to ........ #in one sentence
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@@ -155,5 +151,96 @@ class process_session():
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full_recommendations = full_recommendations.replace('User:', '').strip()
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print("\n")
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print("Full recommendations:", full_recommendations)
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return full_summary, full_recommendations
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triggers_img = Image.open('triggeres.png')
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return triggers_img
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def get_doc_response_emotions(self, user_message, therapy_session_conversation):
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user_messages = []
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user_messages.append(user_message)
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emotion_set = detect_emotions(user_message)
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therapy_session_conversation.append(["User: "+user_message, "Therapist: "+doc_response])
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# session_conversation.extend(["User: "+user_message, "Therapist: "+doc_response])
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print(f"User's message: {user_message}")
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print(f"RAG Matching message: {dials_embeddings.iloc[top_match_index]['Patient']}")
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return '', therapy_session_conversation, emotions_msg
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def summarize_and_recommend(therapy_session_conversation):
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session_conversation = [item[0] for item in therapy_session_conversation]
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session_time = str(datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
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session_conversation_processed = self.session_conversation.copy()
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model="tiiuae/falcon-180b-chat",
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messages=[
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{"role": "system", "content": """You are an Expert Cognitive Behavioural Therapist and Precis writer.
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Summarize 'STRICTLY' the below user content <<<session_conversation_processed>>> 'ONLY' into useful, ethical, relevant and realistic phrases with a format
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Session Time:
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Summary of the patient messages: #in two to four sentences
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Summary of therapist messages: #in two to three sentences:
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model="tiiuae/falcon-180b-chat",
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messages=[
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{"role": "system", "content": """You are an expert Cognitive Behavioural Therapist.
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Based on 'STRICTLY' the full summary <<<full_summary>>> 'ONLY' provide clinically valid, useful, appropriate action plan for the Patient as a bullted list.
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The list shall contain both medical and non medical prescriptions, dos and donts. The format of response shall be in passive voice with proper tense.
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- The patient is referred to........ #in one sentence
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- The patient is advised to ........ #in one sentence
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full_recommendations = full_recommendations.replace('User:', '').strip()
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print("\n")
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print("Full recommendations:", full_recommendations)
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therapy_session_conversation=[]
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return full_summary, full_recommendations
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# class process_session():
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# def __init__(self):
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# self.session_conversation=[]
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# def get_doc_response_emotions(self, user_message, therapy_session_conversation):
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# user_messages = []
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# user_messages.append(user_message)
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# emotion_set = detect_emotions(user_message)
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# print(emotion_set)
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# emotions_msg = generate_triggers_img(emotion_set)
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# user_embedding = embed_model.encode(user_message, device='cuda' if torch.cuda.is_available() else 'cpu')
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# similarities =[]
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# for v in dials_embeddings['embeddings']:
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# similarities.append(cosine_distance(user_embedding,v))
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# top_match_index = similarities.index(max(similarities))
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# # doc_response = dials_embeddings.iloc[top_match_index+1]['Doctor']
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# doc_response = dials_embeddings.iloc[top_match_index]['Doctor']
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# therapy_session_conversation.append(["User: "+user_message, "Therapist: "+doc_response])
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# self.session_conversation.extend(["User: "+user_message, "Therapist: "+doc_response])
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# print(f"User's message: {user_message}")
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# print(f"RAG Matching message: {dials_embeddings.iloc[top_match_index]['Patient']}")
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# print(f"Therapist's response: {dials_embeddings.iloc[top_match_index]['Doctor']}\n\n")
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# return '', therapy_session_conversation, emotions_msg
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# def summarize_and_recommend(self):
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# session_time = str(datetime.now().strftime("%Y-%m-%d %H:%M:%S"))
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# session_conversation_processed = self.session_conversation.copy()
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# session_conversation_processed.insert(0, "Session_time: "+session_time)
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# session_conversation_processed ='\n'.join(session_conversation_processed)
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# print("Session conversation:", session_conversation_processed)
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# full_summary = ""
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# for chunk in AI71(AI71_API_KEY).chat.completions.create(
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# model="tiiuae/falcon-180b-chat",
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# messages=[
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# {"role": "system", "content": """You are an Expert Cognitive Behavioural Therapist and Precis writer.
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# Summarize the below user content <<<session_conversation_processed>>> into useful, ethical, relevant and realistic phrases with a format
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# Session Time:
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# Summary of the patient messages: #in two to four sentences
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# Summary of therapist messages: #in two to three sentences:
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# Summary of the whole session: # in two to three sentences. Ensure the entire session summary strictly does not exceed 100 tokens."""},
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# {"role": "user", "content": session_conversation_processed},
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# ],
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# stream=True,
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# ):
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# if chunk.choices[0].delta.content:
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# summary = chunk.choices[0].delta.content
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# full_summary += summary
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# full_summary = full_summary.replace('User:', '').strip()
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# print("\n")
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# print("Full summary:", full_summary)
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# full_recommendations = ""
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# for chunk in AI71(AI71_API_KEY).chat.completions.create(
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# model="tiiuae/falcon-180b-chat",
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# messages=[
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# {"role": "system", "content": """You are an expert Cognitive Behavioural Therapist.
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# Based on the full summary <<<full_summary>>> provide clinically valid, useful, appropriate action plan for the Patient as a bullted list.
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# The list shall contain both medical and non medical prescriptions, dos and donts. The format of response shall be in passive voice with proper tense.
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# - The patient is referred to........ #in one sentence
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# - The patient is advised to ........ #in one sentence
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# - The patient is refrained from........ #in one sentence
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# - It is suggested that tha patient ........ #in one sentence
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# - Scheduled a follow-up session with the patient........#in one sentence
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# *Ensure the list contains NOT MORE THAN 7 points"""},
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# {"role": "user", "content": full_summary},
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# ],
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# stream=True,
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# ):
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# if chunk.choices[0].delta.content:
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# rec = chunk.choices[0].delta.content
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# full_recommendations += rec
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# full_recommendations = full_recommendations.replace('User:', '').strip()
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# print("\n")
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# print("Full recommendations:", full_recommendations)
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# self.session_conversation=[]
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# return full_summary, full_recommendations
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