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medbot_2

Commit History

Jun 2, 2025

15:02
Update medbot/config.py

techindia2025

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5a2288f

May 28, 2025

07:35
Update medbot/config.py

techindia2025

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7714d19
07:33
Update medbot/config.py

techindia2025

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c3c506c

May 23, 2025

17:25
Increase max_new_tokens in generate method to 1000 for enhanced output capacity

Thanush

dde83e1
17:14
Update interface branding to BluePlanet Medical Assistant

Thanush

a22013f
16:43
Refactor prompts in prompts.py for improved readability and structure

Thanush

4ee00f5
12:48
Fix formatting of FALLBACK_MODEL assignment in config.py

Thanush

96a523f
12:45
Update FALLBACK_MODEL to use ClinicalCamel-13B for improved performance

Thanush

8fb70c8
12:37
Update ME_LLAMA_MODEL to use the Llama-3.1-8B-Instruct variant and improve fallback model logging

Thanush

79da5f0
12:30
update config

Thanush

1d5907c
12:29
Update ME_LLAMA_MODEL to use the 13b variant for improved performance

Thanush

21c51e5
12:22
Update model configurations to use new model paths and adjust tensor data types; increase max_new_tokens and modify sampling parameters in generate method for improved output quality.

Thanush

004c8e7
12:16
model update

Thanush

7e9bd6e
12:11
Update ME_LLAMA_MODEL to use google/medgemma-4b-it for improved performance

Thanush

b5523ff
11:56
model and ui update

Thanush

7c9f8aa
11:38
Update ME_LLAMA_MODEL and refine consultation prompt for clarity and focus

Thanush

b57f649
11:21
Refine consultation prompt for clarity and empathy, ensuring systematic information gathering and avoiding repetitive questions.

Thanush

eafb03b
11:10
Enhance logging in handlers and update consultation prompt for clarity and empathy

Thanush

6daaaf3
09:55
Update max_new_tokens in generate method and enhance consultation prompt for clarity

Thanush

736646e
09:48
Simple prompt update

Thanush

d194416
09:35
Update conversation turn limit and enhance prompts for medical consultation app

Thanush

f2907c6
06:53
add space

Thanush

6e15dcc
06:48
Implement medical consultation app with LangChain memory management and model integration

Thanush

031a3f5
06:48
Add .gitignore file to exclude unnecessary files and directories

Thanush

1bcbb86
06:14
Enhance medical consultation app with LangChain memory management and improved patient context tracking

Thanush

0b85ef5

May 22, 2025

16:49
Update app.py

techindia2025

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10736b1
16:45
Update app.py

techindia2025

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1cb1a8e
16:34
Update app.py

techindia2025

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c66e1bd
16:23
Update app.py

techindia2025

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7dd1c93
16:07
Update requirements.txt

techindia2025

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b6f3058
16:06
Update app.py

techindia2025

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5067011
15:29
Update requirements.txt

techindia2025

Verified signature
d73b8dc
15:28
Update app.py

techindia2025

Verified signature
afe76d4
15:18
Update app.py

techindia2025

Verified signature
1728da9
12:06
Refactor app.py to implement LangChain memory for enhanced conversation tracking. Update prompt building and response generation logic to utilize full conversation context, improving user interaction and medical assessment accuracy.

Thanush

f3b4260
12:01
Refactor SYSTEM_PROMPT in app.py to enhance the medical consultation process with a structured approach for gathering patient information. Update follow-up question guidelines and improve response generation logic for more intelligent interactions.

Thanush

01a984c
11:56
Refactor app.py to streamline user information collection by removing redundant prompts for name and age. Implement a simple state tracking mechanism for improved conversation flow and enhance medical consultation process with structured follow-up questions.

Thanush

43e5827
11:48
Enhance user interaction in app.py by refining follow-up questions for symptom collection and implementing intelligent extraction of user name and age from messages. Improve response generation logic to ensure comprehensive medical assessments and treatment recommendations.

Thanush

a7f6391
11:27
Refactor MEDITRON_PROMPT in app.py to enhance medical assessment and recommendations, ensuring evidence-based practices and clear communication. Update name and age extraction logic for improved accuracy in user responses.

Thanush

5522bf8
11:22
Enhance prompt building in app.py to include intelligent follow-up questions and adjust response generation logic based on user information turns.

Thanush

d6da22c
11:11
Enhance user information collection in app.py by emphasizing follow-up questions and refining response generation logic based on actual information turns.

Thanush

a985489
11:05
Refactor app.py to extract user name and age from conversation history and improve response generation logic

Thanush

000ab02
10:50
Update SYSTEM_PROMPT in app.py for clarity and detail in patient information collection process

Thanush

6e237a4
10:38
Refactor prompt building in app.py to utilize full message sequence and enhance response generation context

Thanush

a0597d0
10:23
Refactor app.py to integrate LangChain memory for conversation tracking and update requirements.txt for LangChain dependency

Thanush

c4447f4
10:04
Update requirements.txt

techindia2025

Verified signature
6196bed
09:53
Refactor app.py to streamline conversation state management and update requirements.txt for package versions

Thanush

aa89cd7
09:48
update meditron

techindia2025

71bcd31
09:38
uppdate app and requirement.txt

techindia2025

9ae5fda
06:01
Update requirements.txt

techindia2025

Verified signature
117a288

Commit History

Jun 2, 2025

Update medbot/config.py

May 28, 2025

Update medbot/config.py

Update medbot/config.py

May 23, 2025

Increase max_new_tokens in generate method to 1000 for enhanced output capacity

Update interface branding to BluePlanet Medical Assistant

Refactor prompts in prompts.py for improved readability and structure

Fix formatting of FALLBACK_MODEL assignment in config.py

Update FALLBACK_MODEL to use ClinicalCamel-13B for improved performance

Update ME_LLAMA_MODEL to use the Llama-3.1-8B-Instruct variant and improve fallback model logging

update config

Update ME_LLAMA_MODEL to use the 13b variant for improved performance

Update model configurations to use new model paths and adjust tensor data types; increase max_new_tokens and modify sampling parameters in generate method for improved output quality.

model update

Update ME_LLAMA_MODEL to use google/medgemma-4b-it for improved performance

model and ui update

Update ME_LLAMA_MODEL and refine consultation prompt for clarity and focus

Refine consultation prompt for clarity and empathy, ensuring systematic information gathering and avoiding repetitive questions.

Enhance logging in handlers and update consultation prompt for clarity and empathy

Update max_new_tokens in generate method and enhance consultation prompt for clarity

Simple prompt update

Update conversation turn limit and enhance prompts for medical consultation app

add space

Implement medical consultation app with LangChain memory management and model integration

Add .gitignore file to exclude unnecessary files and directories

Enhance medical consultation app with LangChain memory management and improved patient context tracking

May 22, 2025

Update app.py

Update app.py

Update app.py

Update app.py

Update requirements.txt

Update app.py

Update requirements.txt

Update app.py

Update app.py

Refactor app.py to implement LangChain memory for enhanced conversation tracking. Update prompt building and response generation logic to utilize full conversation context, improving user interaction and medical assessment accuracy.

Refactor SYSTEM_PROMPT in app.py to enhance the medical consultation process with a structured approach for gathering patient information. Update follow-up question guidelines and improve response generation logic for more intelligent interactions.

Refactor app.py to streamline user information collection by removing redundant prompts for name and age. Implement a simple state tracking mechanism for improved conversation flow and enhance medical consultation process with structured follow-up questions.

Enhance user interaction in app.py by refining follow-up questions for symptom collection and implementing intelligent extraction of user name and age from messages. Improve response generation logic to ensure comprehensive medical assessments and treatment recommendations.

Refactor MEDITRON_PROMPT in app.py to enhance medical assessment and recommendations, ensuring evidence-based practices and clear communication. Update name and age extraction logic for improved accuracy in user responses.

Enhance prompt building in app.py to include intelligent follow-up questions and adjust response generation logic based on user information turns.

Enhance user information collection in app.py by emphasizing follow-up questions and refining response generation logic based on actual information turns.

Refactor app.py to extract user name and age from conversation history and improve response generation logic

Update SYSTEM_PROMPT in app.py for clarity and detail in patient information collection process

Refactor prompt building in app.py to utilize full message sequence and enhance response generation context

Refactor app.py to integrate LangChain memory for conversation tracking and update requirements.txt for LangChain dependency

Update requirements.txt

Refactor app.py to streamline conversation state management and update requirements.txt for package versions

update meditron

uppdate app and requirement.txt

Update requirements.txt