Make all params available for llamacpp api (#1019)

* Make all params available for llamacpp api

* Add prompt prefix and suffix

agixt/providers/llamacppapi.py

@@ -2,36 +2,83 @@
 import random
 
 
+# Instructions for setting up llama.cpp server:
+# https://github.com/ggerganov/llama.cpp/tree/master/examples/server#llamacppexampleserver
 class LlamacppapiProvider:
     def __init__(
         self,
         AI_PROVIDER_URI: str = "http://localhost:8000",
         AI_MODEL: str = "default",
+        PROMPT_PREFIX: str = "",
+        PROMPT_SUFFIX: str = "",
         STOP_SEQUENCE: str = "</s>",
-        MAX_TOKENS: int = 2048,
-        AI_TEMPERATURE: float = 0.7,
-        AI_TOP_P: float = 0.7,
+        MAX_TOKENS: int = 4096,
+        AI_TEMPERATURE: float = 0.8,
+        AI_TOP_P: float = 0.95,
+        AI_TOP_K: int = 40,
+        TFS_Z: float = 1.0,
+        TYPICAL_P: float = 1.0,
+        REPEAT_PENALTY: float = 1.1,
+        REPEAT_LAST_N: int = 64,
+        PENALIZE_NL: bool = True,
+        PRESENCE_PENALTY: float = 0.0,
+        FREQUENCY_PENALTY: float = 0.0,
+        MIROSTAT: int = 0,
+        MIROSTAT_TAU: float = 5.0,
+        MIROSTAT_ETA: float = 0.1,
+        IGNORE_EOS: bool = False,
+        LOGIT_BIAS: list = [],
         **kwargs,
     ):
         self.AI_PROVIDER_URI = (
             AI_PROVIDER_URI if AI_PROVIDER_URI else "http://localhost:8000"
         )
         self.AI_TEMPERATURE = AI_TEMPERATURE if AI_TEMPERATURE else 0.7
         self.AI_TOP_P = AI_TOP_P if AI_TOP_P else 0.7
+        self.AI_TOP_K = AI_TOP_K if AI_TOP_K else 40
         self.MAX_TOKENS = MAX_TOKENS if MAX_TOKENS else 2048
         self.AI_MODEL = AI_MODEL if AI_MODEL else "default"
         self.STOP_SEQUENCE = STOP_SEQUENCE if STOP_SEQUENCE else "</s>"
         self.MAX_TOKENS = int(self.MAX_TOKENS) if self.MAX_TOKENS else 2048
+        self.TFS_Z = TFS_Z if TFS_Z else 1.0
+        self.TYPICAL_P = TYPICAL_P if TYPICAL_P else 1.0
+        self.REPEAT_PENALTY = REPEAT_PENALTY if REPEAT_PENALTY else 1.1
+        self.REPEAT_LAST_N = REPEAT_LAST_N if REPEAT_LAST_N else 64
+        self.PENALIZE_NL = PENALIZE_NL if PENALIZE_NL else True
+        self.PRESENCE_PENALTY = PRESENCE_PENALTY if PRESENCE_PENALTY else 0.0
+        self.FREQUENCY_PENALTY = FREQUENCY_PENALTY if FREQUENCY_PENALTY else 0.0
+        self.MIROSTAT = MIROSTAT if MIROSTAT else 0
+        self.MIROSTAT_TAU = MIROSTAT_TAU if MIROSTAT_TAU else 5.0
+        self.MIROSTAT_ETA = MIROSTAT_ETA if MIROSTAT_ETA else 0.1
+        self.IGNORE_EOS = IGNORE_EOS if IGNORE_EOS else False
+        self.LOGIT_BIAS = LOGIT_BIAS if LOGIT_BIAS else []
+        self.PROMPT_PREFIX = PROMPT_PREFIX if PROMPT_PREFIX else ""
+        self.PROMPT_SUFFIX = PROMPT_SUFFIX if PROMPT_SUFFIX else ""
 
     async def instruct(self, prompt, tokens: int = 0):
         max_tokens = int(self.MAX_TOKENS) - tokens
+        prompt = f"{self.PROMPT_PREFIX}{prompt}{self.PROMPT_SUFFIX}"
         params = {
             "prompt": prompt,
             "temperature": float(self.AI_TEMPERATURE),
             "top_p": float(self.AI_TOP_P),
             "stop": self.STOP_SEQUENCE,
             "seed": random.randint(1, 1000000000),
             "n_predict": int(max_tokens),
+            "stream": False,
+            "top_k": int(self.AI_TOP_K),
+            "tfs_z": float(self.TFS_Z),
+            "typical_p": float(self.TYPICAL_P),
+            "repeat_penalty": float(self.REPEAT_PENALTY),
+            "repeat_last_n": int(self.REPEAT_LAST_N),
+            "penalize_nl": self.PENALIZE_NL,
+            "presence_penalty": float(self.PRESENCE_PENALTY),
+            "frequency_penalty": float(self.FREQUENCY_PENALTY),
+            "mirostat": int(self.MIROSTAT),
+            "mirostat_tau": float(self.MIROSTAT_TAU),
+            "mirostat_eta": float(self.MIROSTAT_ETA),
+            "ignore_eos": self.IGNORE_EOS,
+            "logit_bias": self.LOGIT_BIAS,
         }
         response = requests.post(f"{self.AI_PROVIDER_URI}/completion", json=params)
         data = response.json()