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server/custom_ui.py

@@ -100,7 +100,7 @@ async def handle_ingestion(ref_img, clip_vids, lora, tok, prompt, param_json):
     except Exception as e:
         return f"Exception: {str(e)}\n{traceback.format_exc()}"
 
-async def handle_analysis(ingestion_id, model_id, provider, max_tokens, temp):
+async def handle_analysis(ingestion_id, model_id, provider, api_key, max_tokens, temp):
     if not ingestion_id:
         return "Error: Provide an Ingestion ID first."
     try:
@@ -113,6 +113,8 @@ async def handle_analysis(ingestion_id, model_id, provider, max_tokens, temp):
         }
         if model_id:
             data["model_id"] = str(model_id)
+        if api_key:
+            data["api_key"] = str(api_key)
             
         async with httpx.AsyncClient() as client:
             resp = await client.post(url, json=data, timeout=120.0)
@@ -152,6 +154,7 @@ def build_custom_ui(web_manager, action_fields, metadata, is_chat_env, title, qu
                         analysis_ingestion_id = gr.Textbox(label="Ingestion ID (auto-filled from step 1)")
                         analysis_provider = gr.Dropdown(choices=["auto", "openai", "anthropic", "huggingface", "local"], value="auto", label="LLM Provider")
                         analysis_model = gr.Textbox(label="Model ID (Optional formatting)", placeholder="e.g. meta-llama/Llama-3.1-70B-Instruct")
+                        analysis_api_key = gr.Textbox(label="API Key (Required for HF/OpenAI/Anthropic)", type="password", placeholder="Enter your token here...")
                         analysis_max_tokens = gr.Slider(minimum=64, maximum=4096, value=700, step=1, label="Max Tokens")
                         analysis_temp = gr.Slider(minimum=0.0, maximum=1.0, value=0.2, step=0.01, label="Temperature")
                         
@@ -169,7 +172,7 @@ def build_custom_ui(web_manager, action_fields, metadata, is_chat_env, title, qu
                         
                         analyze_btn.click(
                             handle_analysis,
-                            inputs=[analysis_ingestion_id, analysis_model, analysis_provider, analysis_max_tokens, analysis_temp],
+                            inputs=[analysis_ingestion_id, analysis_model, analysis_provider, analysis_api_key, analysis_max_tokens, analysis_temp],
                             outputs=[analysis_report_out]
                         )