Save Copilot Data to an External Server Endpoint

This example collects all the parameters (the user's query, the bot's answer, WhatsApp number number, etc) from the (copilot)["https://gooey.ai/copilot"] workflow and sends it to an arbitrary endpoint. Alter this example with the REST API of your own server to log every interaction.

⌥ Variables

Pass custom parameters to your function and access the parent workflow data. Variables will be passed down as the first argument to your anonymous JS function. Learn more.

bot_wa_phone_number

conversation_id

integration_id

integration_name

platform

request (JSON)

{
  "tools": [],
  "quality": 1.0,
  "messages": [],
  "asr_model": null,
  "documents": [],
  "functions": [
    {
      "url": "https://gooey.ai/functions/ais-post-copilot-pmqsi0gpv5w7/",
      "trigger": "post"
    }
  ],
  "bot_script": "You are ChatGPT, a large language model trained by OpenAI, based on the GPT-4o architecture.\nKnowledge cutoff: 2023-10 \nCurrent date: {{ datetime.utcnow }}\n\nImage input capabilities: Enabled\n\n{% if platform == \"TWILIO\" %}\nRemember, you are a voice agent, so do not use markdown, HTML, latex or any other markup language, instead, output plain text without any formatting characters like asterisk, hyphen, bracket, hash, underscore etc. Keep your responses concise and clear under 100 words.\n{% endif %}",
  "input_face": null,
  "max_tokens": 4000,
  "input_audio": null,
  "num_outputs": 1,
  "scroll_jump": 5,
  "dense_weight": 1.0,
  "google_pitch": 0.0,
  "input_images": [
    "https://storage.googleapis.com/dara-c1b52.appspot.com/daras_ai/media/7eede9c8-12ab-11ef-acd6-02420a00011f/image.png"
  ],
  "input_prompt": "Files: image.png\n\nRead the text from this image and match the numbers on the scatter plot",
  "tts_provider": null,
  "user_language": null,
  "citation_style": "number_plaintext",
  "document_model": null,
  "max_references": 3,
  "selected_model": "gpt_4_o",
  "input_documents": [
    "https://storage.googleapis.com/dara-c1b52.appspot.com/daras_ai/media/7eede9c8-12ab-11ef-acd6-02420a00011f/image.png"
  ],
  "avoid_repetition": false,
  "elevenlabs_model": "eleven_multilingual_v2",
  "elevenlabs_style": 0.0,
  "face_padding_top": 2,
  "face_padding_left": 0,
  "google_voice_name": "hi-IN-Wavenet-A",
  "max_context_words": 300,
  "task_instructions": "[Guidelines]\n- Use the Search Results to produce a coherent answer.\n- Search results may be incomplete or irrelevant. Don't make assumptions on the Search Results beyond strictly what's returned.\n- If the Search Result's Title or Snippet is unrelated or irrelevant to the question, don't respond and just say you don't know.\n- Never give advice to search the Internet. \n- Leverage information from multiple search results to respond comprehensively\n- Always reference factual statements to the Search Results using [${number}] notation, i.e. square brackets with numerical references to the URLs. e.g. [1], [2], [3], [4], ...\n- You can only issue numerical references to the URLs. Never generate URLs or links or titles.",
  "translation_model": null,
  "use_url_shortener": true,
  "face_padding_right": 0,
  "query_instructions": "<Chat History>\n{{ messages }}\n\n<Instructions> \nGiven the conversation, only rephrase the last message to be a standalone statement in 2nd person's perspective. Make sure you include only the relevant parts of the conversation required to answer the follow-up question, and not the answer to the question. If the conversation is irrelevant to the current question being asked, discard it.\n\n<Standalone Statement>",
  "face_padding_bottom": 10,
  "uberduck_voice_name": "kanye-west-rap",
  "elevenlabs_stability": 0.5,
  "google_speaking_rate": 1.0,
  "keyword_instructions": "",
  "response_format_type": null,
  "sampling_temperature": 0.7,
  "elevenlabs_voice_name": "Rachel",
  "uberduck_speaking_rate": 1.0,
  "input_glossary_document": null,
  "output_glossary_document": null,
  "elevenlabs_similarity_boost": 0.75
}

response (JSON)

{
  "output_text": [
    "Sure, I can help match the numbers from the scatter plot to the text from the image. Here are the matches based on the provided information:\n\n### Leading the Change\n1. **Innovation** - Scale innovation\n2. **Transparency** - Promote transparency\n3. **Engaging Changemakers** - Partner for industrywide progress\n\n### Circular & Climate Positive\n4. **Circular Ecosystems** - Recycled and other sustainably sourced materials\n5. - Animal welfare\n6. - Circular ecosystems for our products, supply chains, and customer journey\n7. - Water\n8. - Waste\n9. - Packaging\n10. - Chemical management\n11. **Climate Positive** - Climate positive approach for our value chain operating within planetary boundaries\n12. **Biodiversity** - Biodiversity\n\n### Fair & Equal\n13. **Fair Jobs for All** - Fair jobs\n14. - Industrial relations\n15. - Fair living wages\n16. **Inclusion and Diversity** - Human rights due diligence\n17. - Inclusion and diversity\n18. - Community development\n\n### Standards & Policies\n19. - Supply chain assessment\n20. - Anti-corruption\n21. - Responsible marketing\n\n### Other Identified Topics\n22. - Anti-competitive behavior\n23. - Economic performance\n24. - Market presence\n\n### Scatter Plot Numbers\n- Top Right Quadrant (High Frequency Raised by Stakeholders, High Significance of Impacts)\n  - 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 20, 21, 23\n- Bottom Right Quadrant (Low Frequency Raised by Stakeholders, High Significance of Impacts)\n  - 15, 18\n- Top Left Quadrant (High Frequency Raised by Stakeholders, Low Significance of Impacts)\n  - None\n- Bottom Left Quadrant (Low Frequency Raised by Stakeholders, Low Significance of Impacts)\n  - 22, 24"
  ],
  "final_prompt": [
    {
      "role": "system",
      "content": "You are ChatGPT, a large language model trained by OpenAI, based on the GPT-4o architecture.\nKnowledge cutoff: 2023-10 \nCurrent date: August 06, 2024 19:54:39 \n\nImage input capabilities: Enabled\n\n"
    },
    {
      "role": "user",
      "content": [
        {
          "type": "image_url",
          "image_url": {
            "url": "https://storage.googleapis.com/dara-c1b52.appspot.com/daras_ai/media/7eede9c8-12ab-11ef-acd6-02420a00011f/image.png"
          }
        },
        {
          "text": "Files: image.png\n\nRead the text from this image and match the numbers on the scatter plot",
          "type": "text"
        }
      ]
    }
  ],
  "finish_reason": [
    "stop"
  ],
  "raw_input_text": "Files: image.png\n\nRead the text from this image and match the numbers on the scatter plot",
  "raw_output_text": [
    "Sure, I can help match the numbers from the scatter plot to the text from the image. Here are the matches based on the provided information:\n\n### Leading the Change\n1. **Innovation** - Scale innovation\n2. **Transparency** - Promote transparency\n3. **Engaging Changemakers** - Partner for industrywide progress\n\n### Circular & Climate Positive\n4. **Circular Ecosystems** - Recycled and other sustainably sourced materials\n5. - Animal welfare\n6. - Circular ecosystems for our products, supply chains, and customer journey\n7. - Water\n8. - Waste\n9. - Packaging\n10. - Chemical management\n11. **Climate Positive** - Climate positive approach for our value chain operating within planetary boundaries\n12. **Biodiversity** - Biodiversity\n\n### Fair & Equal\n13. **Fair Jobs for All** - Fair jobs\n14. - Industrial relations\n15. - Fair living wages\n16. **Inclusion and Diversity** - Human rights due diligence\n17. - Inclusion and diversity\n18. - Community development\n\n### Standards & Policies\n19. - Supply chain assessment\n20. - Anti-corruption\n21. - Responsible marketing\n\n### Other Identified Topics\n22. - Anti-competitive behavior\n23. - Economic performance\n24. - Market presence\n\n### Scatter Plot Numbers\n- Top Right Quadrant (High Frequency Raised by Stakeholders, High Significance of Impacts)\n  - 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 20, 21, 23\n- Bottom Right Quadrant (Low Frequency Raised by Stakeholders, High Significance of Impacts)\n  - 15, 18\n- Top Left Quadrant (High Frequency Raised by Stakeholders, Low Significance of Impacts)\n  - None\n- Bottom Left Quadrant (Low Frequency Raised by Stakeholders, Low Significance of Impacts)\n  - 22, 24"
  ]
}

user_id

user_message_id

user_wa_phone_number

web_url

Run cost = 5 credits

Functions are free if called from another workflow.

By submitting, you agree to Gooey.AI's terms & privacy policy.

Return value

{7 Items

"audio"

NULL

"image"

string

"https://storage.googleapis.com/dara-c1b52.appspot.…"

"question"

string

"Files: image.png Read the text from this image an…"

"response"

string

"Sure, I can help match the numbers from the scatte…"

"conversation_id"

string

"1OwO"

"bot_wa_phone_number"

string

"+45 93 70 64 51"

"user_wa_phone_number"

string

"+91 87640 22384"

}

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Save Copilot Data to an External Server Endpoint

⌥ Variables

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