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import ollama
import chromadb
import speech_recognition as sr
import requests
import pyttsx3
client = chromadb.Client()
message_history = [
{
'id' : 1,
'prompt' : 'What is your name?',
'response' : 'My name is TADBot, a bot to help with short term remedial help for mental purposes. '
},
{
'id' : 2,
'prompt' : 'Bye',
'response' : 'Good to see you get better. Hopefully you reach out to me if you have any problems.'
},
{
'id' : 3,
'prompt' : 'What is the essence of Life?',
'response' : 'The essence of life is to create what you want of yourself.'
}
]
convo = []
modelname = "ms"
def create_vector_db(conversations):
vector_db_name = 'conversations'
try:
client.delete_collection(vector_db_name)
except ValueError as e:
pass
vector_db = client.create_collection(name=vector_db_name)
for c in conversations:
serialized_convo = 'prompt: ' + c["prompt"] + ' response: ' + c["response"]
response = ollama.embeddings(model = "nomic-embed-text",prompt = serialized_convo)
embedding = response["embedding"]
vector_db.add(ids = [str(c['id'])], embeddings = [embedding], documents = [serialized_convo])
def stream_response(prompt):
convo.append({'role': "user", 'content': prompt})
output = ollama.chat(model = modelname, messages = convo)
response = output['message']['content']
print("TADBot: ")
print(response)
engine = pyttsx3.init()
engine.say(response)
engine.runAndWait()
convo.append({'role': "assistant", 'content': response})
def retrieve_embeddings(prompt):
response = ollama.embeddings(model = "nomic-embed-text", prompt = prompt)
propmt_embedding = response['embedding']
vector_db = client.get_collection(name = 'conversations')
results = vector_db.query(query_embeddings=[propmt_embedding], n_results = 1)
best_embedding = results['documents'][0][0]
return best_embedding
create_vector_db(message_history)
while True:
r = sr.Recognizer()
m = sr.Microphone()
try:
print("Say something!")
with m as source:
audio = r.listen(source)
try:
# for testing purposes, we're just using the default API key
# to use another API key, use `r.recognize_google(audio, key="GOOGLE_SPEECH_RECOGNITION_API_KEY")`
# instead of `r.recognize_google(audio)`
prompt = r.recognize_google(audio)
print("Tadbot thinks you said: " + prompt)
except sr.UnknownValueError:
print("Tadbot could not understand audio")
except sr.RequestError as e:
print("Could not request results from Google Speech Recognition service; {0}".format(e))
print("Please wait...")
with m as source:
r.adjust_for_ambient_noise(source)
if prompt == "bye" or prompt == "Bye":
print("TADBot: Hopefully I was able to help you out today. Have a Nice Day!")
break
"""
context = retrieve_embeddings(prompt)
prompt = prompt + "CONTEXT FROM EMBEDDING: " + context
"""
stream_response(prompt)
except KeyboardInterrupt:
pass
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