Cdb fix

.gitignore

@@ -39,3 +39,7 @@ spring_ai/create_user.sql
 spring_ai/drop.sql
 start.sh
 spring_ai/env.sh
+temp/rag_agent.ipynb
+temp/tools.ipynb
+temp/tools.py
+temp/json-dual.sql

README.md

@@ -52,6 +52,12 @@ To run the application on bare-metal; download the [source](https://github.com/o
    pip3 install -r app/requirements.txt
    ```
 
+1. Exit from your shell and run again:
+
+   ```bash
+   source .venv/bin/activate
+   ```
+
 1. Start Streamlit:
 
    ```bash

app/requirements.txt

@@ -14,7 +14,7 @@
 bokeh==3.6.1
 evaluate==0.4.3
 faiss-cpu==1.9.0
-giskard==2.15.5
+giskard==2.15.2
 IPython==8.29.0
 langchain-cohere==0.3.1
 langchain-community==0.3.7

app/src/content/test_framework.py

@@ -188,10 +188,6 @@ def main():
     st_common.set_default_state("test_set", None)
     st_common.set_default_state("temp_dir", None)
 
-    # TO CHECK
-    # file_path = "temp_file.csv"
-    # if os.path.exists(file_path):
-    #    os.remove(file_path)
 
     if state.toggle_generate_test:
         st.header("Q&A Test Dataset Generation")
@@ -256,6 +252,8 @@ def main():
             # Generate Q&A
             qa_file = os.path.join(state["temp_dir"], f"{file_name}_{str(qa_count)}_test_set.json")
             state.qa_file = qa_file
+            logger.info("calling generate with client: ")
+            logger.info(llm_client)
             state.test_set = utilities.generate_qa(qa_file, kb, qa_count, client=llm_client)
             placeholder.empty()
             st.success("Q&A Generation Succeeded.", icon="✅")

app/src/modules/report_utils.py

@@ -129,12 +129,12 @@ def record_update():
     # Text input for the question, storing the user's input in the session state
     state.index_output = st.write("Record: " + str(state.index + 1) + "/" + str(state.df.shape[0]))
     state.hide_input = st.checkbox("Hide", value=state.hide_input)
-    state.question_input = st.text_area("question", height=1, value=state.question_input)
-    state.reference_answer_input = st.text_area("Reference answer", height=1, value=state.reference_answer_input)
+    state.question_input = st.text_area("question", height=100, value=state.question_input)
+    state.reference_answer_input = st.text_area("Reference answer", height=100, value=state.reference_answer_input)
     state.reference_context_input = st.text_area(
-        "Reference context", height=10, value=state.reference_context_input, disabled=True
+        "Reference context", height=100, value=state.reference_context_input, disabled=True
     )
-    state.metadata_input = st.text_area("Metadata", height=1, value=state.metadata_input, disabled=True)
+    state.metadata_input = st.text_area("Metadata", height=100, value=state.metadata_input, disabled=True)
 
     if save_clicked:
         st.success("Q&A saved successfully!")

app/src/modules/st_common.py

@@ -437,8 +437,13 @@ def create_zip(state_dict_filt, provider):
 def check_hybrid_conf(session_state_json):
 
     chatModel = state.ll_model_config.get(session_state_json["ll_model"])
-    embModel = state.embed_model_config.get(state.rag_params["model"])
 
+    if "rag_params" in state and "model" in state.rag_params:
+        embModel = state.embed_model_config.get(state.rag_params["model"])
+    else:
+        # Handle the case where rag_params or "model" key does not exist
+        embModel = None  # or some default value
+
     logger.info("Model: %s",session_state_json["ll_model"])
     logger.info("Embedding Model embModel: %s",embModel)
     logger.info("Chat Model: %s",chatModel)

app/src/modules/utilities.py

@@ -82,7 +82,8 @@ def get_ll_model(model, ll_models_config=None, giskarded=False):
     lm_params = ll_models_config[model]
 
     logger.info(
-        "Configuring LLM - URL: %s; Temp - %s; Max Tokens - %s",
+        "Configuring LLM - Model: %s; URL: %s; Temp - %s; Max Tokens - %s",
+        model,
         lm_params["url"],
         lm_params["temperature"][0],
         lm_params["max_tokens"][0],
@@ -115,7 +116,7 @@ def get_ll_model(model, ll_models_config=None, giskarded=False):
     elif llm_api == "ChatPerplexity":
         client = ChatPerplexity(pplx_api_key=lm_params["api_key"], model_kwargs=common_params)
     elif llm_api == "ChatOllama":
-        client = ChatOllama(base_url=lm_params["url"], model_kwargs=common_params)
+        client = ChatOllama(model=model,base_url=lm_params["url"], model_kwargs=common_params)
     ## End - Add Additional Model Authentication Here
     api_accessible, err_msg = is_url_accessible(llm_url)
 

widget/app.js

@@ -63,7 +63,8 @@ document.addEventListener('DOMContentLoaded', () => {
             });
 
             const data = await response.json();
-            return data.choices[0].message.content;
+            return data.answer;
+            //return data.choices[0].message.content;
         } catch (error) {
             console.error('Error fetching API:', error);
             return "Sorry, I couldn't connect to the server.";