add history with function
Browse files- .gitignore +162 -0
- app.py +24 -19
- config.yaml +3 -0
- requirements.txt +2 -1
.gitignore
ADDED
@@ -0,0 +1,162 @@
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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dist/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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nosetests.xml
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coverage.xml
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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#Pipfile.lock
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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# https://pdm.fming.dev/#use-with-ide
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.pdm.toml
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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celerybeat-schedule
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celerybeat.pid
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*.sage.py
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ENV/
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env.bak/
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.mypy_cache/
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.dmypy.json
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dmypy.json
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.DS_Store
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app.py
CHANGED
@@ -7,6 +7,7 @@ GROQ_API_KEY = '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'
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client = Groq(api_key=GROQ_API_KEY)
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MODEL = "llama-3.1-70b-versatile"
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def calculate(expression):
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"""Evaluate a mathematical expression"""
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try:
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except:
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return json.dumps({"error": "Invalid expression"})
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def chatbot(user_prompt):
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tools = [
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{
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"type": "function",
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}
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]
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messages = [
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]
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response = client.chat.completions.create(
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model=MODEL,
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messages=messages,
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tools=tools,
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tool_choice="auto",
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max_tokens=4096
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)
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response_message = response.choices[0].message
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model=MODEL,
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messages=messages
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)
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return second_response.choices[0].message.content
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else:
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return
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# Create Gradio interface with examples
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"50 % 3"
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]
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interface = gr.Interface(
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fn=
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inputs="text",
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outputs="text",
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title="
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examples=examples
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)
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# Launch Gradio app
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interface.launch()
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client = Groq(api_key=GROQ_API_KEY)
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MODEL = "llama-3.1-70b-versatile"
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+
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def calculate(expression):
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"""Evaluate a mathematical expression"""
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try:
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except:
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return json.dumps({"error": "Invalid expression"})
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def chatbot(user_prompt, history=[]):
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tools = [
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{
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"type": "function",
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}
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]
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messages = history + [
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{
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"role": "system",
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"content": "You are a assistant. You can Use the calculate function to perform mathematical operations and provide the results or Answer question that is not mathematical question."
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},
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{
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"role": "user",
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"content": user_prompt,
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}
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] # Start with the system message and append the history
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response = client.chat.completions.create(
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model=MODEL,
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messages=messages,
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tools=tools,
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tool_choice="auto",
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)
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response_message = response.choices[0].message
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model=MODEL,
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messages=messages
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)
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return second_response.choices[0].message.content, messages[1:] # Return updated history
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else:
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return response.choices[0].message.content, messages[1:]
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# Create Gradio interface with examples
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"50 % 3"
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]
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def gradio_chatbot(user_prompt, history=[]):
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response, new_history = chatbot(user_prompt, history)
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return response, new_history
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interface = gr.Interface(
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fn=gradio_chatbot,
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inputs=["text", "state"],
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outputs=["text", "state"],
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title="Groq Chatbot",
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examples=examples
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)
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# Launch the Gradio app
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interface.launch()
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config.yaml
ADDED
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GROQ:
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key: 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
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model: llama-3.1-70b-versatile
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requirements.txt
CHANGED
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huggingface_hub==0.22.2
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groq
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huggingface_hub==0.22.2
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groq
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gradio
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