Cotran/hallucination integration (#115)

* fix fc integration

* fix integration

* remove file

* Update arch_fc.py

* create model server hallucination detection class

model_server/app/main.py

@@ -190,6 +190,40 @@ async def zeroshot(req: ZeroShotRequest, res: Response):
         "model": req.model,
     }
 
+
+class HallucinationRequest(BaseModel):
+    prompt: str
+    parameters: dict
+    model: str
+
+
+@app.post("/hallucination")
+async def hallucination(req: HallucinationRequest, res: Response):
+    """
+        Hallucination API, take input as text and return the prediction of hallucination for each parameter
+        parameters: dictionary of parameters and values
+            example     {"name": "John", "age": "25"}
+        prompt: input prompt from the user
+    """
+    if req.model not in zero_shot_models:
+        raise HTTPException(status_code=400, detail="unknown model: " + req.model)
+
+    classifier = zero_shot_models[req.model]
+    candidate_labels = [f"{k} is {v}" for k, v in req.parameters.items()]
+    hypothesis_template = "{}"
+    result = classifier(
+        req.prompt, candidate_labels=candidate_labels, hypothesis_template=hypothesis_template, multi_label=True
+    )
+    result_score = result['scores']
+    result_params = {k[0]: s for k, s in zip(req.parameters.items(), result_score)}
+
+    return {
+        "params_scores": result_params,
+        "raw_result": result,
+        "model": req.model,
+    }
+
+
 @app.post("/v1/chat/completions")
 async def chat_completion(req: ChatMessage, res: Response):
     result = await arch_fc_chat_completion(req, res)

model_server/openai_params.yaml

@@ -2,5 +2,5 @@ params:
   temperature: 0.01
   top_p : 0.5
   top_k: 50
-  max_tokens: 512
+  max_tokens: 2024
   stop_token_ids: [151645, 151643]