Update app.py
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app.py
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import openai
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import requests
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def interpret_prompt(prompt):
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# Call GPT model
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response =
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model="gpt-4",
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messages=[
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)
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return response.choices[0].message
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def post_to_erp(accounting_entry):
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#
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response = requests.post(url, json=accounting_entry, headers=headers)
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return response.json()
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prompt = "Received $245 from Tylor Smith today"
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interpretation = interpret_prompt(prompt)
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result = post_to_erp(accounting_entry)
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print(result)
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import openai
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import requests
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# Initialize OpenAI client
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client = openai.OpenAI(api_key="YOUR_API_KEY") # Replace with your real API key
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def interpret_prompt(prompt):
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# Call OpenAI GPT model
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response = client.chat.completions.create(
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model="gpt-4", # You can also use "gpt-3.5-turbo" if preferred
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messages=[
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{"role": "user", "content": prompt}
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]
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)
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return response.choices[0].message.content
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def map_to_journal_entry(interpretation):
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"""
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This is a placeholder function.
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In real implementation, parse 'interpretation' to map correct accounts and amounts.
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For demo, returning dummy entry.
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"""
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return {
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"date": "2025-05-02",
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"journal_id": 1, # Example journal
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"lines": [
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{"account_id": 101, "debit": 0, "credit": 245, "partner": "Tylor Smith"}, # AR
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{"account_id": 201, "debit": 245, "credit": 0, "partner": "Tylor Smith"} # Bank/Cash
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]
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}
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def post_to_erp(accounting_entry):
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url = "https://your-odoo-instance.com/api/account.move" # Replace with your Odoo API endpoint
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headers = {
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"Authorization": "Bearer YOUR_ODOO_API_TOKEN",
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"Content-Type": "application/json"
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}
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response = requests.post(url, json=accounting_entry, headers=headers)
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return response.json()
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# Example user prompt
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prompt = "Received $245 from Tylor Smith today"
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# Step 1: Interpret prompt
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interpretation = interpret_prompt(prompt)
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print("AI Interpretation:", interpretation)
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# Step 2: Map to journal entry
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accounting_entry = map_to_journal_entry(interpretation)
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print("Mapped Entry:", accounting_entry)
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# Step 3: Post to ERP
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result = post_to_erp(accounting_entry)
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print("ERP API Response:", result)
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