groqqer is a lightweight, zero-dependency Go OpenAI-compatible API gateway and proxy for the Groq Streamlit chatbot space (https://dromerosm-groq-chatbot.hf.space).

It converts standard OpenAI chat completions and model requests into automated headless browser interactions, providing fast inference with Groq models without requiring an API key.

Features

OpenAI Compatible API: Exposes standard /v1/models and /v1/chat/completions endpoints. Drop-in replacement for OpenAI SDKs, Open-WebUI, LiteLLM, LibreChat, and LangChain.
Zero Third-Party Dependencies: Written entirely in pure Go using only the standard library (net/http, encoding/json, os/exec, crypto/rand, etc.). Includes a built-in RFC 6455 WebSocket CDP client and RFC 1928 SOCKS5 proxy client.
System Prompt Support: Translates developer/system messages into natural instruction framing.
Streaming & Non-Streaming: Supports Server-Sent Events (stream: true) with real-time token delivery, as well as synchronous JSON responses.
Tool / Function Calling: Fully supports OpenAI tools, tool_choice, and multi-turn execution (role: "tool"). Automatically injects schemas and parses <tool_call> responses into OpenAI tool_calls payloads with finish_reason: "tool_calls".
Reasoning Content: Automatically parses <think> and </think> tags from reasoning models (such as Qwen 3.6/3.8) and streams or populates reasoning_content in accordance with OpenAI O-series conventions.
Dynamic Model Discovery: Scrapes active models directly from the Streamlit UI on startup and allows seamless model switching between requests (qwen/qwen3.6-27b, openai/gpt-oss-120b, openai/gpt-oss-20b, groq/compound, etc.).
Display Isolation via Xvfb: Automatically discovers and spawns a virtual X display (:100 - :199) to keep browser automation completely isolated from host desktop displays. Gracefully falls back to offscreen coordinates if Xvfb is not present.
SOCKS5 Proxy Tunneling: Tunnel browser traffic through SOCKS5 proxies using the -socks flag or ALL_PROXY / SOCKS5_PROXY environment variables.
Clean Session Isolation: Automatically clears Streamlit conversation state between requests to prevent cumulative token window exhaustion or stale error states.

Architecture

+---------------------------+
| OpenAI Client / SDK / App |
+---------------------------+
              |  HTTP POST /v1/chat/completions
              v
+---------------------------+
|          groqqer          |
|  (Pure Go Standard Lib)   |
+---------------------------+
              |  RFC 6455 WebSocket CDP
              v
+---------------------------+
|    Chromium / Chrome      |
| (Display :100+ via Xvfb)  |
+---------------------------+
              |  HTTPS
              v
+---------------------------+
|   Groq Streamlit Space    |
| (dromerosm-groq-chatbot)  |
+---------------------------+

Requirements

Linux (x86_64 or aarch64)
Go 1.20+
Chromium or Google Chrome installed (/usr/bin/chromium, /usr/bin/google-chrome, or in $PATH)
(Optional) Xvfb (xorg-server-xvfb) for display isolation

Installation & Build

Clone or navigate to the repository, then build the binary:

make

The optimized binary will be placed at bin/groqqer.

Running the Server

Start the gateway with default settings:

./bin/groqqer -port 8080

CLI Flags

Flag	Default	Description
`-port`	`8080`	HTTP server listening port
`-target`	`https://dromerosm-groq-chatbot.hf.space`	Target Groq Streamlit space URL
`-default-model`	`llama-3.3-70b-versatile`	Fallback model if request does not specify one
`-browser`	`""`	Custom path to Chromium/Chrome binary
`-xvfb`	`true`	Enable virtual X server display isolation
`-no-xvfb`	`false`	Disable virtual X server (run offscreen)
`-socks`	`""`	SOCKS5 proxy URL (e.g. `socks5://127.0.0.1:1080`)
`-user-agent`	(Chrome 133 UA)	Custom browser User-Agent string

API Usage Examples

1. List Available Models

curl -s http://127.0.0.1:8080/v1/models

Response:

{
  "object": "list",
  "data": [
    {"id": "qwen/qwen3.6-27b", "object": "model", "created": 1788869470, "owned_by": "groq"},
    {"id": "openai/gpt-oss-120b", "object": "model", "created": 1788869470, "owned_by": "groq"},
    {"id": "openai/gpt-oss-20b", "object": "model", "created": 1788869470, "owned_by": "groq"},
    {"id": "groq/compound", "object": "model", "created": 1788869470, "owned_by": "groq"}
  ]
}

2. Chat Completion (Non-Streaming)

curl -s -X POST http://127.0.0.1:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen3.6-27b",
    "messages": [
      {"role": "system", "content": "You are a concise assistant. Reply in one sentence."},
      {"role": "user", "content": "What is the capital of France?"}
    ]
  }'

Response:

{
  "id": "chatcmpl-9691bbf8-8623-4155-a40f-a00e6b6903ac",
  "object": "chat.completion",
  "created": 1788869478,
  "model": "qwen/qwen3.6-27b",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "The capital of France is Paris.",
        "reasoning_content": "Analyze User Input: Question: 'What is the capital of France?'..."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 0,
    "completion_tokens": 0,
    "total_tokens": 0
  }
}

3. Streaming Chat Completion (SSE)

curl -N -s -X POST http://127.0.0.1:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen3.6-27b",
    "messages": [
      {"role": "user", "content": "Count from 1 to 4 with commas."}
    ],
    "stream": true
  }'

Output:

data: {"id":"chatcmpl-341d6d05","object":"chat.completion.chunk","created":1788869487,"model":"qwen/qwen3.6-27b","choices":[{"index":0,"delta":{"role":"assistant"}}]}

data: {"id":"chatcmpl-341d6d05","object":"chat.completion.chunk","created":1788869487,"model":"qwen/qwen3.6-27b","choices":[{"index":0,"delta":{"reasoning_content":"Thinking process..."}}]}

data: {"id":"chatcmpl-341d6d05","object":"chat.completion.chunk","created":1788869487,"model":"qwen/qwen3.6-27b","choices":[{"index":0,"delta":{"content":"1, 2, 3,"}}]}

data: {"id":"chatcmpl-341d6d05","object":"chat.completion.chunk","created":1788869487,"model":"qwen/qwen3.6-27b","choices":[{"index":0,"delta":{"content":" 4"}}]}

data: {"id":"chatcmpl-341d6d05","object":"chat.completion.chunk","created":1788869487,"model":"qwen/qwen3.6-27b","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}

data: [DONE]

4. Tool / Function Calling

curl -s -X POST http://127.0.0.1:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen3.6-27b",
    "messages": [
      {"role": "user", "content": "What is the current weather in Tokyo?"}
    ],
    "tools": [
      {
        "type": "function",
        "function": {
          "name": "get_current_weather",
          "description": "Get current weather for a city",
          "parameters": {
            "type": "object",
            "properties": {
              "location": {"type": "string", "description": "The city and country, e.g. Tokyo, Japan"}
            },
            "required": ["location"]
          }
        }
      }
    ],
    "tool_choice": "auto"
  }'

Response:

{
  "id": "chatcmpl-cb050ba0-2573-403f-a1db-e76cdfb8f99d",
  "object": "chat.completion",
  "created": 1788869493,
  "model": "qwen/qwen3.6-27b",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": null,
        "tool_calls": [
          {
            "id": "call_ff437271",
            "type": "function",
            "function": {
              "name": "get_current_weather",
              "arguments": "{\"location\":\"Tokyo, Japan\"}"
            }
          }
        ]
      },
      "finish_reason": "tool_calls"
    }
  ]
}

5. Multi-Turn Tool Response Execution

Once you run your tool locally, send the tool result back using role: "tool":

curl -s -X POST http://127.0.0.1:8080/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen3.6-27b",
    "messages": [
      {"role": "user", "content": "What is the current weather in Tokyo?"},
      {
        "role": "assistant",
        "tool_calls": [
          {
            "id": "call_ff437271",
            "type": "function",
            "function": {
              "name": "get_current_weather",
              "arguments": "{\"location\":\"Tokyo, Japan\"}"
            }
          }
        ]
      },
      {
        "role": "tool",
        "tool_call_id": "call_ff437271",
        "name": "get_current_weather",
        "content": "{\"temperature\": \"18°C\", \"condition\": \"Sunny\", \"humidity\": \"45%\"}"
      }
    ]
  }'

Response:

{
  "id": "chatcmpl-aad3ed3e-b401-41b8-9b3b-a9455070def5",
  "object": "chat.completion",
  "created": 1788869501,
  "model": "qwen/qwen3.6-27b",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "It is currently sunny in Tokyo with a temperature of 18°C and 45% humidity."
      },
      "finish_reason": "stop"
    }
  ]
}

Python OpenAI SDK Example

from openai import OpenAI

client = OpenAI(
  base_url="http://127.0.0.1:8080/v1",
  api_key="not-needed"
)

response = client.chat.completions.create(
  model="qwen/qwen3.6-27b",
  messages=[
    {"role": "system", "content": "You are a helpful coding assistant."},
    {"role": "user", "content": "Write a Python function to reverse a string."}
  ]
)

print(response.choices[0].message.content)

License

MIT License