keep chat model up to date (#148)

nuclia · Jan 29, 2025 · 1efd95a · 1efd95a
1 parent fccd42e
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -3,7 +3,8 @@
 ## 4.4.9 (unreleased)
 
 
-- Nothing changed yet.
+- Keep ChatModel up to date
+- Fix nuclia nua chat format error
 
 
 ## 4.4.8 (2025-01-28)

diff --git a/docs/10-activity-log.md b/docs/10-activity-log.md
@@ -95,31 +95,6 @@ The `audit_metadata` field is a customizable dictionary. Use the `key` operator
   }
 }
 ```
-### Special Field: `audit_metadata`
-The `audit_metadata` field is a customizable dictionary. Use the `key` operator to target specific keys within the dictionary.
-
-#### Example to filter by `audit_metadata`:
-
-```json
-{
-  "year_month": "2024-10",
-  "show": ["audit_metadata.environment"],
-  "filters": {
-    "audit_metadata": [
-      {
-        "key": "environment",
-        "eq": "prod"
-      }
-    ]
-  },
-  "pagination": {
-    "limit": 10
-  }
-}
-```
-
-
-
 
 ### Download Examples
 

diff --git a/nuclia/lib/nua_chat.py b/nuclia/lib/nua_chat.py
@@ -72,7 +72,7 @@ def _process_messages(self, messages: list[dict[str, str]]) -> tuple[str, str]:
 
             if role == "system":
                 system_messages.append(content)
-            elif role == "user":
+            else:
                 user_messages.append(content)
 
         formatted_system = "\n".join(system_messages) if system_messages else ""
@@ -110,6 +110,7 @@ def completion(
             system=system_prompt,
             user_prompt=UserPrompt(prompt=user_prompt),
             query_context={},
+            format_prompt=False,
         )
         response: GenerativeFullResponse = self.predict_sync.generate(
             text=body,

diff --git a/nuclia/lib/nua_responses.py b/nuclia/lib/nua_responses.py
@@ -84,13 +84,24 @@ class ChatModel(BaseModel):
     truncate: Optional[bool] = False
     user_prompt: Optional[UserPrompt] = None
     citations: Optional[bool] = False
+    citation_threshold: Optional[float] = Field(
+        default=None,
+        description="If citations is set to True, this will be the similarity threshold. Value between 0 and 1, lower values will produce more citations. If not set, it will be set to the optimized threshold found by Nuclia.",
+        ge=0.0,
+        le=1.0,
+    )
     generative_model: Optional[str] = None
     max_tokens: Optional[int] = None
     query_context_images: Union[
         List[Image], Dict[str, Image]
     ] = {}  # base64.b64encode(image_file.read()).decode('utf-8')
     prefer_markdown: Optional[bool] = None
     json_schema: Optional[Dict[str, Any]] = None
+    format_prompt: bool = True
+    rerank_context: bool = Field(
+        default=False,
+        description="Whether to reorder the query context based on a reranker. This option will also make it so the first response will contain the scores given for each context piece.",
+    )
 
     @model_validator(mode="after")
     def validate_model(self) -> Self: